What is Prospect Intelligence Scoping?

Our new skill takes your ICP and walks you through a structured process to establish: where do those folk hang out (LinkedIn, Slack communities, email lists, specific industries)? What’s the best way for you to reach each one individually? It tests each assumption against real data before you commit to outreach.

As always with BoS OS, you, the human, are in charge.

The output is a working prospect list. Not a spreadsheet of guesses. Not LinkedIn filters. A list of people who match your ICP, with a mapped route to reach each one individually (email address, LinkedIn profile, mutual connection, event they’re attending).

You can route and monitor follow-ups in the BoS OS and existing systems. Once you’ve run it, you have a repeatable process. When your ICP sharpens (and it will, because every customer conversation teaches you something), you run the skill again. You scale what works.

This doesn’t replace your instinct or your sales skill. It removes the manual research work so you can focus on the conversations that matter. You spend time on people worth reaching, contacted through the channel that works for them.

Install Prospect Intelligence Scoping from BoS OS Advancing Skills.

Let us know what you think, suggest another skill or submit your own.

I had no idea what BoS OS was when I joined. I’d used Claude before, sure, but just on my own, for my own stuff, no different from how a lot of people are dipping their toes into AI right now, half curious and half unsure it was worth the time. Then I walked into Business of Software right in the middle of a much bigger shift, one that started after a talk from Tim Barker got everyone in the room thinking differently about what AI could actually do for a company like ours. That talk is part of why BoS OS exists in the first place. I just happened to show up while it was still being built.

No map, no handover

Nobody handed me a system on day one. Jann was out on maternity leave. Mark was buried in conference prep. The person who had my role before me had one week left before she was gone. Great timing all around. There was no drive with everything sorted. No map of how anything worked. I inherited a pile of systems nobody had time to walk me through, and I did not know where to start.

There was no proper system yet, so I built one for myself, temporarily, just to keep things moving while we figured out the real one. We’re still figuring it out, honestly. The first thing I actually wrote down was our passwords. Not exactly the heroic starting point you’d expect.

The real work started with a meeting.

No onboarding doc existed. So I made one live, during the call, asking every question I had while someone answered. Whatever came back, I typed straight into a Google Doc as we talked.

That document got me through those first weeks. I built it out of pure necessity, not because anyone told me to.

Making the system fit me

Even with that doc, BoS OS itself felt like a lot to take in, the whole way we worked had changed at once, and some days I couldn’t tell what my actual job was anymore.

Then Mark said something that stuck: BoS OS is supposed to make our lives easier, not add more work on top. I stopped trying to force myself to fit the system and started making the system fit me instead.

I have ADHD, and a wall of text will lose me every time. So I told the OS how I needed it to talk to me: plain language first, the simple version before the technical one, and show me, don’t just tell me, because staring at pure text for too long pulls me somewhere else entirely. I built myself a dashboard where every task lives, and I cross it off when it’s done. Watching that happen gives me a kind of satisfaction a text reply never did. I even taught it to call a hard stop when I’ve hit my limit for the day, because left on its own, AI will happily pull you down a rabbit hole for hours and act like that’s normal.

That is when BoS OS stopped being something I opened and used. It started working with how my brain actually runs, and started helping me decide instead of just answering.

What’s still unfinished

We are still fixing things. Naming conventions are half sorted. Sync issues are getting better but not solved. What is different is what the process itself surfaced: parts of BoS that had been broken for a long time and nobody had noticed, workarounds nobody questioned, extra steps that never needed to exist. Building this properly meant we couldn’t look away from any of that.

My own role got clearer too. I know what is mine to own, what BoS OS can carry for me, and what still needs my hands on it directly. The manual grind that used to eat my whole day is mostly gone now. What is left is room to actually work on growing BoS instead of just keeping it standing.

If you’re new somewhere and you got handed a mess with no map, I get it. I wasn’t trying to fix anything. I just needed a way through mine.

If you’re staring down that same pile with no map, that’s exactly what the Introduction to BoS OS workshop is for. Two sessions, real example, no jargon required to start.

Jason Cohen’s BoS talk, “Escaping the Growth Ceiling,” takes that excuse away in the first few minutes.

His diagnosis is simpler and a lot less comfortable. You hit a mathematical ceiling. You were always heading toward it. You just never ran the numbers that would have told you it was coming.

Jason walks through the mechanics using real data from Buffer and ConvertKit, showing how the math works against you by default, and what the companies that break through actually do differently.

I’m still new to marketing, so a lot of what I’ve learned so far is the “just post more, try more channels” school of thought. This talk was the first time someone showed me why that advice runs out of road on its own.

Marketing grows linearly, cancellations grow exponentially.

How you get customers and how you lose them are two completely different shapes.

Marketing is linear. Even when you optimize your channels, you add a roughly steady number of new users each month. Draw it on a graph and it’s a straight line.

Cancellations are exponential. This is the part that sneaks up on you. Churn is a percentage of your total base, so the bigger you get, the bigger that number gets too.

As Jason puts it: “Marketing grows linearly. Cancellations grow exponentially. That’s what a percentage is.”

Say you have 1,000 customers and 5% monthly churn. That’s 50 people gone a month. If marketing brings in 100 new users, you’re still up 50. Feels fine. Feels like you’ve cracked it.

Now triple the business. 3,000 customers. Same marketing engine, still pulling in 100 new users a month. But 5% churn on 3,000 is 150 people. You’re now shrinking by 50 a month, and marketing didn’t change at all. Nobody did anything wrong. The math just caught up.

The Ceiling Has a Number: Max MRR

Jason’s fix for founders flying blind is a metric he calls Max MRR. It’s the revenue ceiling your business hits once cancellations catch up to acquisition.

Max MRR = New MRR per month ÷ Monthly Churn Rate

Bring in £150k in new MRR a month with 5% churn, and your ceiling is £3 million. You can throw every ad dollar you have at it and you’ll still hit that wall.

This isn’t theoretical. Buffer lived through a hard 5% churn rate for years. Joel Gascoigne told that whole recovery story at BoS too, and you can see the ceiling sitting right there in their graphs the entire time. ConvertKit went the other way: a decade of work to grind churn down to 3%, which is what let them keep climbing instead of stalling out.

Max MRR moves months before your actual revenue chart shows anything wrong. It’s an early warning, if you’re watching it. I didn’t even know this was a number you could calculate before this talk, and now I keep wondering how many teams find out their ceiling exists only after they’ve already hit it.

Your Cancellation Survey Is Lying to You

When revenue dips, the instinct is to dig into the cancellation survey. Don’t bother. Most of those dropdowns are noise. People click whatever’s first just to get past the popup.

Open ended, casual questions work far better. Groove tested this. They switched the automated email subject line to a plain “quick question,” and got a 10% usable response rate. Then they changed the actual question from “Why did you cancel?” to “What made you cancel?” Same idea, softer framing. Response rate doubled to 20%.

But even good feedback has a trap built in. When someone writes “too expensive,” we panic and reach for the pricing page. Jason’s counter is simple. They already agreed the price was fair the day they entered their card details.

“Too expensive” is usually a translation of something else. A value drop that happened weeks earlier. Confusing onboarding, a feature that didn’t work right, a workflow that felt like friction. It wasn’t price. Value stopped showing up. The fix was never in the pricing page. It was in something that happened quietly, weeks before anyone typed “cancel.”

The real fix is catching people on the happy path, the sequence a healthy, sticking around user actually follows. Someone who falls off that path hasn’t decided to leave yet. They’re just lost. Wait until they hit cancel and you’ve already lost the window. Fix the onboarding instead, and it compounds across every cohort after it, because the steepest drop off is always right at the start.

Three Ways Out

These are the three levers Jason points to for breaking the ceiling instead of hitting it.

1. Give and get referrals. Skip the one way cash incentive. Dropbox’s “we both get extra space” reads like a favor between friends, not a commission pitch.
2. Net Revenue Retention above 100%. This is the real lever. Above 100% NRR, upgrades from your existing base outpace what churn takes away, and the business starts compounding on its own. Dropbox has been acquiring fewer new customers year over year and still growing revenue, because the existing base carries it.
3. Show your receipts. Remind customers what you’re doing for them before the invoice lands. A security dashboard that says “blocked 5,000 attacks for you this month” builds the case for you. So when a price increase shows up later, it feels earned instead of random.

The full talk is on the BoS website. Watch it alongside Joel Gascoigne’s companion talk on Buffer’s recovery to see these ideas actually play out.

Jason Cohen

Jason has  built four software startups, both bootstrapped and funded, both alone and with co-founders. All of them grew to more than $1m annual revenue.He sold two, and currently serves as CTO of the fourth, WPEngine, with 380 employees headquartered in Austin, Texas.  More recently, he has also been an angel investor and was a founding member of Capital Factory, an Austin incubator and co-working space. He writes about software and startups at ASmartBear.

More from Jason.

A ChatGPT or Claude subscription someone uses for drafting. Copilot in the codebase. Maybe a chatbot on the website that was set up and then quietly forgotten. A few team members who’ve found prompts they like and use them for specific tasks. A Slack thread somewhere with “useful AI prompts” that nobody’s looked at in three months.

That’s not an operating system. That’s a drawer full of tools.

And the difference between a drawer full of tools and an operating system is roughly the difference between a 1x business and a 5x business.

Tim Barker, former CMO at Salesforce and CEO of a 600-person healthcare company, now running a five-person AI-native startup, spent seven months building the latter from scratch. He came to Business of Software Europe 2026 to explain what it actually involves.

The answer is not more tools. It’s not better prompts. It’s a system. And most businesses don’t have one yet.

What an AI Operating System Actually Is

The analogy Tim reaches for is a new hire.

Imagine bringing on the most brilliant person you’ve ever hired. Extraordinary capability. Across every function. Available instantly, at any hour, at a cost that would have seemed impossible five years ago.

There’s one problem: they wake up every morning with no memory of what happened yesterday. No institutional knowledge. No recollection of the decision made in last Tuesday’s leadership meeting, or the pricing change from three weeks ago, or the brand positioning you’ve been refining for six months.

So how do you manage that person effectively?

You’d do what you do with every high-performing hire. You’d onboard them properly. You’d give them your strategy, your values, your brand standards, your products, the markets you serve and those you don’t. You’d give them a clear role with explicit boundaries. Not vague, not broad, but specific enough that they know exactly what authority they have and when a decision needs to come back to you. You’d give them work to do, review their output, and build a feedback loop that makes their next output better than their last.

“You do all of this today,” Tim told the BoS Europe audience. “The great thing about building an AI-first system is you just need to institute all of these things in a way that AI can use them.”

That’s an AI operating system. It’s not software you buy. It’s organisational infrastructure you build.

The Architecture: Five Layers

Tim’s operating system lives in a folder structure. Five layers, each serving a specific purpose, each feeding into the others.

Strategy is the foundation. Your brand, your values, your products, your priorities for the year, the markets you serve. Everything that probably exists somewhere on a shared drive, probably stale, that every employee should know but most don’t fully. This is your first task: pull it together, refresh what’s out of date, and format it so AI can read it.

“It’s a good opportunity to refresh these things before you start feeding them in,” Tim noted. Most organisations discover that articulating their strategy clearly enough for AI to use it reveals gaps that existed long before AI was in the picture.

Agents is where the job specs live. Each agent has a defined role, clear constraints, and an explicit understanding of what decisions it can make independently and what requires human sign-off. Tim has 14 agents operating today. Some do work: writing, analysis, monitoring. Others are guardians, whose job is to check the work of the agents that produce it.

“Build guardians that check the work of agents,” he said. “You don’t want an agent having growth at any cost. You’ve got to balance it against trust and economics.”

Missions are time-bounded projects: the things you’re actively working on right now, with defined outcomes and deliverables. The output of one mission can become the input to another. Keeping missions discrete keeps token costs manageable and keeps agents focused.

State is your current reality: where the business is today, what decisions have been made, what’s in progress, what’s blocked. This is the layer that most businesses building with AI completely skip. That’s why their AI experience feels like Groundhog Day.

“Context rot is real,” Tim said. “Token windows are only so long. You need to make sure you are always compounding everything back into assets that AI can read every morning.”

Artifacts is the library of approved outputs (content, analysis, frameworks) that feeds back into the system as inputs for future work.

The Layer Most Businesses Are Missing: State

If there’s one thing Tim’s talk made clear, it’s that state management is the difference between AI that learns and AI that resets.

Every leadership meeting at Attain IP is recorded. A few hours after it ends, an agent processes the recording, extracts decisions, and presents Tim with a structured list to review. The ones he approves go into a decision log: a running timeline of every significant call the leadership team has made. That log gets fed back into the context that every agent reads when it starts a new session.

So when an agent wakes up tomorrow, it already knows about the pricing decision from last week, the hiring choice from three weeks ago, the new market focus from last month. It doesn’t need to be told. It reads the state, updates its context, and starts from an informed position rather than a blank slate.

Without this, you’re not building organisational intelligence. You’re re-explaining your business to a very capable but perpetually amnesiac contractor, every single day, from scratch.

Feedback Loops: Where the Compounding Happens

Tools produce outputs. Systems compound learning. The gap between them is feedback loops.

Tim gave a specific example. His agents write content in his voice and in the voices of his co-founders. Every time an agent produces a draft and a revised version gets approved, the system logs the gap between the two, capturing what changed and why. Over time, the gap narrows. The output gets closer to what Tim would have written himself, without Tim having to explain his preferences from scratch each time.

“There is a compounding effect if you just do this on all the assets you produce or draft over time.”

Another example: his LinkedIn monitoring agent delivers ten engagement recommendations every morning at 8am. His co-founder, a patent attorney of 30 years and not particularly active on LinkedIn, reads them, then replies to the agent’s daily email with feedback: which ones she’ll use, which ones missed the mark and why. The next morning, the agent has incorporated that feedback. The recommendations improve. The process costs $0.20 a day.

That’s not a magic prompt. That’s a system that gets better because it has a mechanism for getting better.

The Hard Constraints Your System Needs From Day One

Tim learned this one the expensive way.

Early in building Attain IP, he asked an AI agent with browser access to stub out some LinkedIn ad campaign skeletons, just placeholders he’d optimise and launch properly later. He didn’t specify that the agent wasn’t authorised to spend money. The agent set everything up, switched the campaigns on, and spent $2,000 on traffic to a staging website before Tim noticed three weeks later.

The AI did exactly what it was asked to do. There was no bug. The problem was the absence of a constraint.

“Make it super crisp,” he said of agent instructions. “That’s what’s going to make the whole system efficient and effective.”

Every AI operating system needs hard constraints embedded from the start: what agents can spend, what they can publish, what they can send, what they can change. Not as a brake on capability, but as the governance layer that makes expanding capability trustworthy over time.

The Difference Between a Copilot and an Autopilot

Tim draws a distinction that matters a great deal in practice.

A copilot AI works with you: it produces something, you review it, you approve it, it ships. An autopilot runs without you: it produces, decides, and acts. Both have their place. The question is whether you’ve built enough trust in the system, through enough real-world iteration, to remove yourself from a particular loop.

“Move at the speed of trust,” he said. “I’m not yet at a point where I want agents interacting with prospects and customers directly – until I’ve got their tone of voice to a point where I’m happy with it.”

The path from copilot to autopilot runs through the feedback loop. You review, you feed back, the system improves, you review less frequently, you eventually hand off the loop entirely. That progression is only possible if you built the feedback mechanism in the first place.

Where to Start

Tim’s advice for founders who want to build this is practical and unambiguous.

First: do it yourself. “All of you as leaders cannot delegate this.” Build something: a personal project, a single-function prototype, that forces you to encounter the real problems directly. Not to evaluate AI. To understand it from the inside.

Second: start with your strategy layer. Pull together the documents that define your organisation: brand, values, positioning, priorities. Ask honestly whether they’re current enough to be useful. This is foundational. Everything else builds on it.

Third: define one agent’s role precisely. Not broadly (“help with marketing”) but specifically (“monitor LinkedIn conversations in this domain, score them against these criteria, surface ten recommendations each morning, send to this email address”). Crisp role definition is the hardest part and the most important part.

Fourth: build the state layer before you need it. The decision log, the session summaries, the current priorities. Set up the infrastructure to capture this before there’s urgent content to capture. The habit is the thing.

Build Your AI Company Operating System

Tim Barker walks through the full architecture in the Business of Software workshop specifically designed for this: strategy layer, agents, guardians, missions, state management, and feedback loops.

→ Build Your AI Company Operating System

Tim Barker spoke at Business of Software Europe 2026. His talk drew on seven months of building Attain IP, an AI-native legal tech business, after leaving the CEO role at a 600-person digital healthcare company.

It’s not technophobia. Most founders who’ve built software businesses are not afraid of new technology. It’s something more specific, and actually quite reasonable.

You’ve seen the hype cycles before. You’ve watched tools get adopted across your industry with breathless enthusiasm, only to discover that the ROI was questionable, the implementation was painful, and the main beneficiaries were the vendors. You’ve built a business on judgment, not trends. You’ve learned to be sceptical of things that promise to change everything.

And now you’re watching every conference, every newsletter, every LinkedIn feed fill up with AI content, most of it superficial, much of it plainly wrong, and something in you is saying: wait.

That instinct is not wrong. But it may be leading you to the wrong conclusion.

What You’re Actually Resisting

Tim Barker was honest with the Business of Software Europe 2026 audience about his own version of AI scepticism. Not about whether AI is real, but about the quality of what’s being said about it.

“When you spend your time online, there’s a lot of people talking about AI, but how you implement it in an organisation is a bit hard to find. You’ve got so many people that are just giving you magic prompts that you should be using. It’s not really the answer.”

He’s right. Most AI content is either breathless promotion or useless generality. The 30-prompt lists. The “AI will replace your whole team” takes. The case studies that leave out everything that went wrong. The consultants who’ve never built anything with it telling you how to transform with it.

Resisting that is rational. The mistake is when the resistance extends beyond the noise to the underlying reality.

Because the underlying reality, built by practitioners actually running businesses on this, is considerably less hype-dependent and considerably more durable than the content ecosystem around it suggests.

The Legitimate Concerns, Addressed

Concern #1: “What if it goes wrong and damages our brand or our customer relationships?”

This is the right question, and the answer isn’t “don’t use AI.” It’s “build guardians.”

Tim runs four AI guardian agents whose sole job is to check the work of his other agents before anything goes external. Brand and messaging consistency. Trust implications. Information security. Financial commitments. Nothing reaches a customer or a prospect without passing through at least one check that isn’t the same agent that produced it.

“Move at the speed of trust,” he told the BoS Europe audience. “I’m not at a point where I want agents interacting with prospects and customers directly, until I’ve got their tone of voice to a point where I’m happy with it.”

The answer to “what if it goes wrong” is governance, built in from day one, not bolted on after something breaks.

Concern #2: “What if we become dependent on a vendor and they change pricing or go down?”

This one came up directly from the floor at BoS Europe. An audience member asked Tim: does your business grind to a halt when Anthropic’s servers are down?

“Anthropic or ChatGPT down is the new ‘internet’s down,'” he said. “Nothing happens when they’re down. We’re just reviewing specs that AI produced for us.”

On pricing: Claude’s tokens cost more from 1pm onwards, when the US market is awake. Tim’s adaptation? Schedule the heavy compute work for mornings. The economic model is changing. Surge pricing is coming, just as it did with cloud infrastructure before it. The response is operational adjustment, not abstention.

The organisations that avoided cloud infrastructure because of vendor dependency concerns aren’t looking clever today.

Concern #3: “We don’t have the engineering capacity to build AI systems properly.”

Tim’s response to this one is practical: you probably don’t need as much engineering as you think, and the AI tools available to non-engineers have changed the calculus significantly.

He used Google Stitch, which he calls “the Figma of AI,” to design an app from a written specification, then fed that into Claude Code to build it. A few hours of work, no dedicated engineering resource.

The barrier to building AI-augmented systems is lower than it’s been at any point in the history of building software. That cuts both ways: it lowers the barrier for you, and it lowers the barrier for everyone competing with you.

The Risk You’re Not Accounting For

Founders who resist AI tend to be running a specific mental calculation: the risk of getting AI wrong versus the benefit of getting it right.

What that calculation systematically underweights is the risk of standing still.

“The cost of production is now collapsing relatively compared to how it used to be,” Tim said. “The bar is continually getting reset on how you raise and what progress you need to have.”

This is the part that’s hardest to see from the outside. Seed-stage businesses are now arriving at the milestones that used to require a Series B, because AI has removed the engineering headcount that used to be the rate-limiting step. The companies doing this aren’t announcing it loudly. They’re just shipping.

If you’re in a market where a competitor figures out a 3-5x productivity multiplier before you do, the compounding effect of that advantage over 18-24 months is not recoverable with a catch-up programme. You can’t retro-compound a feedback loop.

The Difference Between Caution and Paralysis

Tim is not reckless about AI. He lost $2,000 because he let an agent operate without the right financial constraints. He talks openly about the mistakes he made and the governance gaps he’s had to close.

He does not advocate for moving fast and breaking things. He advocates for moving at the speed of trust, which means starting, building carefully, establishing what the system can do reliably, and expanding autonomy from there.

“You still need governance structures. But once you’ve got that governance in place, over time, you can apply different levels of depth of governance in some areas where you can autopilot, and others where you want to keep very close to it.”

That’s not an argument for abandoning caution. It’s an argument for applying caution in a way that still produces movement, rather than using caution as a reason not to start.

The founders who will have the worst of both worlds are the ones who wait until the risk of not acting becomes undeniable, and then try to implement fast, without the governance infrastructure, making the exact expensive mistakes that careful early movers already worked through.

The Right Question Isn’t “Should We Use AI?”

It’s “what’s our governance model for how we use it?”

That’s the question worth spending time on. And that’s the conversation the Build Your AI Company Operating System workshop is designed to have starting 20 May, with practitioners who’ve built the guardrails, made the mistakes, and can show you what a trustworthy AI operating model actually looks like.

→ Join the workshop

Tim Barker spoke at Business of Software Europe 2026. He is the founder of Attain IP, a legal tech business applying AI to patents and intellectual property. He previously served as CMO at Salesforce Europe and as CEO of a 600-person digital healthcare company.

Giselle had just joined the team. Jann was on maternity leave. I needed to onboard Giselle fast, hand off Jann’s context, and figure out how we’d work together short-term. All in the run up to a conference. Our onboarding docs were out of date, probably had been for years. We needed something that reflected how we actually work, not how we worked three years ago.

Tim’s insight cut through everything I’d been reading about AI:

Ignore AI. Start with the System.

Every company runs on the same basic structure. Strategy. Roles. Active projects. Outputs. Most founders have all of this. It’s mostly undocumented, siloed, or living inside someone’s head.

If you overlay AI on a system you haven’t mapped, you don’t get clarity. You get speed in every direction.

Speed is not Velocity.

Map the system first. Then overlay agents.

What surprised me: the benefit isn’t just AI governance. When you have to articulate how your company actually works, everything else gets sharper too. Onboarding becomes real. Decisions get logged. Context doesn’t evaporate when someone leaves or joins.

We’re still early. But it’s already changed how BoS operates.

Join us

Not about the after-party. About one talk – Tim Barker’s session on building an AI operating system for your business. Founders wanted to know where to go next. How to start. Whether there was somewhere to actually work through this with people taking it as seriously as they were.

So we built two workshops. Here’s what they are.

What these workshops are not

They are not a survey of AI tools. They are not a keynote stretched into a webinar. They are not a vendor pitch with an agenda stapled to it.

There will be no magic prompts. No breathless forecasting about where AI is heading. No frameworks being sold, no sponsor content.

That’s not us, and it’s not Tim Barker.

Who Tim Barker is, and why it matters

Tim has founded five startups and seen the startup journey from every angle. He sold his first company to Salesforce. He’s taken companies through scale to IPO and led them to several hundred people. He’s been a member of the BoS community for fifteen years.

About nine months ago, he made a deliberate decision: to build his current company, Attain IP, as an AI-native business from day zero. Not AI-assisted. AI-native. He rebuilt how his organisation makes decisions, how it coordinates work, how it delegates and reviews – everything – around a documented operating system that AI agents can actually run inside.

His talk at BoS Europe 2026 was the distillation of that nine-month experiment. The reaction from a room full of founders who had heard every AI pitch going: “someone actually doing it.”

That reaction created these workshops.

The Two Workshops

Workshop 1: AI in Your Business: Where to Start

Two sessions. One week. A first-version OS written down for the first time.

This is for founders who know AI matters and haven’t yet built anything systematic around it. You may be using tools here and there. You may have played with Claude. But nothing has compounded. Every session starts from scratch. You’re still the one holding it all together.

In two sessions across one week, you’ll see exactly how a company OS gets built in practice – then build a first version for yours. Not a template to fill in. A first draft, built from your own business context, challenged by eleven other founders doing the same work in parallel.

By the end of Session 2 you’ll have: a bootstrapped Agent OS, a correction list (the context your tools need that no public source contains), a revised CLAUDE.md (the standing brief your tools read at the start of every session), and a clear path forward – whether that’s building independently or joining the four-week cohort.

• Format: 2 live sessions with Tim Barker and Mark Littlewood
• Cohort: Max 12 founders — no observers, no spectators
• Dates: 13 May + 16 May 2026 · 11am UK

You’ll need Claude Desktop and a Claude Pro or Team plan (required for Cowork mode). If you’re not already using Claude in some capacity, this workshop isn’t the right starting point.

Reserve one of 12 seats →

Questions about fit? Email mark@businessofsoftware.org

Workshop 2: Build Your AI Company Operating System

Four weeks. One operating system each.

This is for founders who are already in motion – already using AI tools, already tinkering – and have hit the ceiling that only a documented OS can break through. You’re not getting less done. You’re amplifying a mess instead of a system.

Over four weekly sessions, with Tim and eleven other founders at exactly the same ceiling, you’ll build yours. Not in theory. Live, in the sessions, challenged each week by the group.

By the end you’ll have: your AI company operating system (the documented rules, constraints, and decision boundaries your agents read at every session), five to eight strategy documents ready to delegate, one fully specified agent (decision boundary, escalation triggers, evaluation framework – ready to run), and a Phase 1 mission your agent can start executing the Monday after the workshop ends.

• Format: 4 live sessions, weekly, with Tim Barker and Mark Littlewood
• Cohort: Max 12 founders – no observers, no spectators
• Dates: Starting Wednesday 20 May · Weekly · 11am UK

You’ll need Claude Desktop, a Claude Pro or Team plan, and to already be using Claude in your business. If you haven’t started yet, Workshop 1 is the right first step.

Reserve one of 12 seats →

Questions about fit? Email mark@businessofsoftware.org

Why a cohort?

The cohort format is deliberate. Peer quality is part of what you’re paying for – a room where almost every conversation is worth having.

You’re not just learning from Tim. You’re learning from eleven other founders who are grappling with the same problems from different angles, with different businesses, at the same stage. That friction is where the most useful thinking happens.

Both cohorts are capped at 12. That’s not a marketing tactic. It’s how you keep the quality of the room.

The BoS No Quibble Guarantee

If you attend either workshop and feel you didn’t get value, we will refund your fee. No questions asked. This is the same guarantee that applies to every BoS event.

Which one is right for you?

• AI in Your Business: Where to Start is the right choice if you haven’t yet built anything systematic with AI in your business – or if you’ve been using tools but nothing has compounded.
• Build Your AI Company Operating System is the right choice if you’re already using Claude or similar tools regularly and want to build the governing structure underneath them – the documented OS that lets everything else finally run without you holding it together.

If you’re genuinely unsure, email Mark: mark@businessofsoftware.org

AI in Your Business: Where to Start – 13 + 16 May · 12 seats

Build Your AI Company Operating System – From 20 May · 12 seats

Business of Software has connected founders and operators with the people who can actually help them build better businesses since 2007. These workshops are built on the same principle as every BoS event: real practitioners, honest conversation, and work that compounds.

“We’re heads down on the product right now.” Or: “Our engineering team is already using Copilot, so we’re covered.” Or the most common one: “We’ll get to it properly once we’ve got past this quarter.”

You’re not alone. Most founders are saying some version of this. And that’s exactly the problem.

Tim Barker spent 20 years building SaaS businesses. He scaled a company from 100 to 600 people and $80 million in revenue. He knows how founders think, because he was one for a long time.

And in April 2026, standing at Business of Software Europe, he said something that should make every founder who’s been putting this off sit up:

“I honestly thought that in two or three years, my currency in SaaS would run to zero. I’ve got to reinvent myself for this next chapter.”

That’s not a warning from an AI evangelist with something to sell. That’s a practitioner who’s spent seven months inside an AI-native business, watching the gap open up between companies that moved and companies that waited.

The Gap Is Already Opening

Here’s what’s happening right now, whether you’re watching it or not.

AI-native companies, some of them five people, are shipping the output that a 25 to 35-person team would have shipped 18 months ago. Seed-stage startups are arriving at Series B milestones before they’ve raised their first proper round. The bar for what “promising early traction” looks like has permanently shifted, because the cost of building to that traction has collapsed.

“The first thing you probably always do when you’re looking at a new organisation on LinkedIn is you go look at the insights and see how many people there are in the business. It gives you a good proxy for how successful they are,” Tim told the BoS Europe audience. “Not anymore.”

If your competitors have figured this out before you, they’re not just moving faster on one feature. They’re moving faster on every front at once: marketing, operations, sales pipeline, product iteration, with a fraction of the team you think they need to be doing all of that.

And here’s the uncomfortable part: you won’t see it coming until the gap is significant. Because these organisations don’t look different from the outside until suddenly they do.

“But We’re Already Using AI”

This is usually where the pushback comes.

Yes, your engineers are using Copilot. Yes, you’ve got a ChatGPT subscription in the marketing team. Yes, someone ran a few experiments with a chatbot on the website last year.

That’s not what we’re talking about.

Tim is explicit that engineering is the one area he’s not going to address, because AI in engineering is “a well-trodden pathway” and if you’re not using it already, you should be by now. The harder, more important question is everything else: marketing, operations, sales, product strategy, leadership decision-making.

Most founders have handed the AI question to their CTO and considered it done. What they’ve actually done is handle 20% of the opportunity and ignored the other 80%.

The Real Cost of Waiting

Every month you don’t build an AI operating system into your business is a month your competitors might be compounding a learning advantage you can’t buy back.

Here’s what Tim built in seven months with five people:

Fourteen AI agents, each with a clear role and defined boundaries. Four guardian agents that check the work of the others. A daily marketing analyst that monitors LinkedIn conversations and surfaces relevant engagement opportunities at 8am every morning, costing $0.20 a day. An automated leadership meeting processor that captures every decision, updates a decision log, and feeds that context back into the AI’s working memory so it’s never starting from scratch. A growth marketing agent that runs ego-free analysis of every experiment, every day, with no one in the room with a vested interest in one campaign over another.

This isn’t science fiction. This is what a small, well-run team can build right now. The agents get better. The feedback loops tighten. The organisation learns.

Why Founders Keep Putting It Off

It’s worth being honest about why this keeps not happening.

Some of it is genuine busyness: there’s always something more urgent than a strategic transformation. Some of it is delegation, assuming the CTO has it, or that a future hire will own it. Some of it is genuine uncertainty about where to start, and a reasonable fear of getting it badly wrong.

But some of it is something harder to admit: the suspicion that if this is real, it threatens the model you’ve spent years building. The team you’ve assembled. The playbooks you know work. The instincts you’ve honed over a career.

Tim gets that. He chose to walk away from the obvious next chapter (another PE-backed business, a portfolio of board seats) precisely because he recognised that his accumulated SaaS expertise had a shortening shelf life. He went all in on learning something new, from scratch, in a startup, at a point in his career where that was a risky choice.

Most founders won’t make that call. But most founders could take the first step.

What the First Step Actually Looks Like

It’s not a transformation programme. It’s not a working group or a governance framework or a six-month evaluation plan.

“Build something yourself,” Tim said. “All of you as leaders cannot delegate this.”

A passion project. Something small and low-stakes that forces you to use the tools, understand the capabilities, and feel what the feedback loop actually does. Tim’s building a running app for himself. Not because it matters to the business. Because it makes him a practitioner, not just a sponsor.

From there: one experiment, with one function leader, with a 30-day horizon. Not to evaluate AI. To deploy something, learn from it, and make the next decision with real data rather than a theoretical assessment.

“This year is the year I hope all of you have got AI transformation in your top three priorities,” Tim said at BoS Europe. “If you haven’t, talk to me afterwards – because you need to start the journey at an organisational level, not just an engineering level.”

The founders who’ll look back on 2026 as the year they figured this out aren’t the ones who’ve been studying it the longest. They’re the ones who stopped waiting for a more convenient moment.

This Is Exactly What We’re Working Through in the Workshops

The Business of Software Build Your AI Company Operating System workshop is where practitioners like Tim share what actually moved the needle, and what to skip.

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Not sure where to start? AI in Your Business: Where to Start live online workshop is built for founders at the moment of deciding this matters.

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Tim Barker spoke at Business of Software Europe 2026. He is the founder of Attain IP, an AI-native legal tech business, and a former CMO at Salesforce and CEO of a 600-person digital healthcare company.

This week, founders, CEOs, and product builders from across the globe made their way to Cambridge, UK for BoS Europe 2026. Two days of honest talks, unhurried conversations, and the kind of community that makes you realise you’re not figuring this out alone.

Sunday — Before it all began

For those who arrived early, Sunday was an unhurried start. A group gathered at the Porters’ Lodge at Churchill College for the Cambridge photo walk, winding through the city at a relaxed pace with a coffee stop halfway. No agenda, no slides. Just a chance to meet people before the conference noise kicked in.

The Local Corner
This year’s Local Corner was one for the books. Attendees brought a little piece of home: chocolate, biscuits, sweets, and snacks from wherever they’d travelled from. It became one of those quiet BoS traditions that somehow says more about the community than any slide deck could.

Free book giveaway
Mark Sherwood-Edwards, an attendee and also the author of The Sales-Side Lawyer: Faster Deals, Increased Revenue, and Goodbye to the Sales Prevention Department handed out copies of the book during the event. Useful reading for any founder who’s ever lost a deal in legal.

Day 1 — Monday, 13 April

The morning kicked off with registration, breakfast, and the first round of Birds of a Feather discussions. If you’ve been to BoS before, you know: the breakfast tables are where some of the best conversations happen. Topics ranged from growth and hiring to the usual question of whether the thing you’re building actually deserves to exist.

MORNING SESSIONS

April Dunford — The Hard Parts of Positioning

Executive consultant and author, Obviously Awesome

April opened the conference with something many founders quietly dread confronting: their positioning probably isn’t as strong as they think it is. Drawing on 11 years and over 300 technology companies, she walked through four recurring positioning challenges, from misidentifying competitive alternatives to what she calls “product pessimism,” when teams are too close to their own work to see its real strengths.

“Your biggest positioning problem isn’t your messaging. It’s the assumptions underneath it that nobody has stopped to question.”

Vince Darley — Extreme Clarity. Relentless Focus.

Product & Growth, former Meta, Deliveroo, King

Vince has led teams of 10 to 1,000 across some of the most demanding product environments in the world. His message was disarmingly simple: most companies take on too much, and it kills them slowly. He shared his iterative process for finding extreme clarity using nothing more than a blank whiteboard, and made the case for a very tight focus on delivering a few things, fast.

“Taking on too much isn’t ambition. It’s the most common way companies quietly destroy themselves.”

Bruce McCarthy — From Product Managers to Product Builders

Founder, Product Culture

AI isn’t just changing the tools product teams use. It’s changing what product organisations are. Bruce made a clear-eyed case that as coding becomes cheaper and faster, the value of roles focused mainly on feeding work to engineers is quietly diminishing. The real constraint moves to strategy, judgment, and leadership.

“When execution gets cheap, the only thing that compounds in value is judgment. Empower the people who have it.”

LUNCH & BREAKOUTS

Lunch at BoS is never just lunch. The dining room filled with Birds of a Feather tables, each one pulling a different thread from the morning. After lunch, attendees spread into breakout rooms and hallways for the Meet the Speakers sessions, where the real interrogation begins.

AFTERNOON SESSIONS

Joanna Wiebe — The Art and Science of Copywriting

Founder, Copyhackers

Joanna is the inventor of conversion copywriting and has spent two decades helping companies including AWS and Canva write copy that actually moves people. Her central point: copy that sounds good and copy that sells are not the same thing. She shared her proven framework for customer-centric messaging, including how to skip the brainstorming entirely and go straight to what your customers are already saying. Her upcoming book, The Copyselling System, lands in July 2026.

“Stop writing from your own head. Your customers have already told you exactly what to say. You just need to listen.”

Shawn Anderson — Building B2B Ecosystems

Co-founder & ex-CEO, PDQ

Shawn bootstrapped PDQ from necessity — no one would fund them — to a PE-backed company serving SysAdmins across the world. His talk explored how PDQ built one of the strongest and most active B2B communities around a user base that, on the surface, seemed to have little in common beyond the software.

“An ecosystem makes a strong SaaS unstoppable. A shaky one, it’ll break. Know which one you have before you build.”

End of Day 1

Networking drinks back in the Buttery Bar, then dinner in the dining hall. By this point the room had that particular BoS energy: people who arrived as strangers now deep in conversation about the things that actually matter. The kind of evening that runs later than planned.

Day 2 — Tuesday, 14 April

BoS Shirt Day & the Class Photo

Tuesday is shirt day. Whether it was a worn-in favourite from a few years back or this year’s fresh one, everyone pulled on their BoS gear for the class photo. A tradition that somehow keeps getting better as the class gets bigger.

Breakfast and another round of Birds of a Feather discussions got the morning going. By day two the tables had a different feel — people picking up where they left off the night before, going deeper on the things that had been rattling around since yesterday.

MORNING SESSIONS

Melanie Rieback — Non-Extractive Business and Finance

CEO, Radically Open Security

Melanie founded Radically Open Security, a company that donates 90% of its profit to charity, and in 2025 launched Non-Extractive Capital to help entrepreneurs pursue alternative business models. Her talk was a systems-level challenge to the current orthodoxy, making the case that rethinking governance structures and financial incentives isn’t just idealism.

“The way most businesses are structured actively encourages harm. Changing that isn’t naive. It’s the most practical thing you can do.“

Tim Barker — AI, Worthless SaaS Playbooks and Redundant Org Charts

CEO & Co-Founder, Attain IP

Tim has founded five startups and sold one to Salesforce. His talk this year asked a different question: what happens if you’re AI-native from day zero? He shared hands-on how he runs product, marketing, and operations with a small team and a fleet of AI agents, including the $2,000 LinkedIn mistake that taught him why guardrail agents matter. His honest assessment of what experienced founders now need to unlearn was one of the most talked-about sessions of the conference.

“Your hardest-won leadership instincts might be the next thing you need to unlearn. AI doesn’t just change what you build. It changes how many people you need to build it.”

Ton Dobbe — Is Your Company Remarkable?

Founder, Value Inspiration

Ask a software CEO how differentiated their company is and they’ll say seven out of ten. Then ask how long it would take a competitor to replicate it. Three weeks. Maybe two sprints. Ton has spent 30 years studying what separates the software companies people genuinely talk about from the ones that compete on price. Attendees scored themselves live. The contradictions were instructive.

“Most companies aren’t as remarkable as they think. The gap between “differentiated” and “genuinely different” is where growth hides.”

LUNCH & BIRDS OF A FEATHER TABLES

Lunch on day two always hits differently. There’s a looseness to it — the conference is nearly over and people are trying to squeeze in the last few conversations they haven’t had yet. The Birds of a Feather tables, breakout rooms and hallways were as busy as ever.

AFTERNOON SESSIONS

Stephen Allott — Financial Planning and the Theory of Constraints 2.0

Chairman, Tarigo

Stephen built Micromuse, the most valuable organically grown UK software company, to NASDAQ IPO and has advised nine unicorns as Venture Partner Emeritus at Seedcamp. His session offered a practical modelling framework based on Goldratt’s Theory of Constraints, focused on identifying the few variables that actually limit scale and connecting every metric directly to a decision you’d actually make.

“Most dashboards measure what’s easy to count. The ones that matter measure the handful of things that, if they moved, you’d actually do something different.”

Lizzie Lawley — The New Product Velocity

Head of Applied AI, Memrise; Founder, Wombat

Lizzie shared Memrise’s two-year journey answering a deceptively simple question: how can AI actually help us and our customers make progress? The honest version included developer resistance, fear of replacement, and plenty of junior-school experimentation before anything clicked. The result: a team that moved from an 18-month feature freeze to shipping multiple AI-driven products, some built entirely by non-technical staff, generating meaningful revenue.

“The bottleneck was never the technology. It was the culture. Change that first, and the velocity follows.”

Dr. Ian Bailey — You Control Your Destiny — Startup Myth Busted

Co-CEO & CTO, Telicent

Ian co-founded Telicent at the start of lockdown, tried and failed to raise VC funding, and built a profitable, sustainable open source business anyway. His talk traced how his thinking evolved as the company grew, shrank, and grew again.

“The most liberating thing you can do as a founder is stop treating the company as your baby. It was never just yours to control.”

LIGHTNING TALKS

And then it was over

Closing drinks in the Buttery Bar. The usual mix of people wrapping up the last conversation they started three hours ago, swapping details, and making entirely sincere plans to stay in touch. Mark, somewhere in the room, likely in a Reese’s suit.

The Magic of BoS

Every BoS conference brings exceptional content. But the real magic is harder to schedule. It’s in the Birds of a Feather tables at breakfast, the hallway conversations that run ten minutes over, the book corner, and the Local Corner table where someone’s brought biscuits from Edinburgh or chocolate from São Paulo.

It’s also in the smaller things: a Reese’s suit, a class photo, a free book that ends up dog-eared before you’ve even left Cambridge.

A massive thank you to our speakers for giving so generously of their time and thinking. And a special thank you to our conference supporters, without whom none of this would be possible.

See you next time.

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