Boards are asking every CEO the same question: what is our plan for AI? The pressure is real, and so is the risk. But the risk isn't moving slowly. It's spending on the wrong things.
Most AI plans begin in the wrong place. They start from a tool, a demo or a handful of senior opinions, and work backwards to a problem. Discovery, the part meant to find out how the work really gets done, is slow and manual: weeks of workshops and reading documents, with a few voices standing in for everyone. What comes out is usually a report. It hears only some of the people, goes out of date quickly, and can't be built from.
That's the gap Reccie was built to close. We call what it does agentic discovery, for evidence-led AI growth.
What we mean by agentic discovery
Agentic discovery is discovery run by AI agents that hear everyone who does the work, check what they hear against each other, and turn it into a ranked plan of what to build.
In Reccie, four agents share that work:
- Scout talks with the people who do the work, in Teams, a browser, by voice, text, phone or email, on their own time. It asks one or two questions at a time, follows the person's lead rather than a script, and comes back over days or weeks when there's more to learn. It only asks. It never advises.
- Lens analyses each conversation as it arrives, maps the process layer by layer, and checks each finding against what others said. Where people disagree, the disagreement is kept, not averaged away.
- Arc proposes builds from the findings, ranks them on impact and effort with their dependencies, and groups them into a first wave.
- Pulse answers questions about the evidence, and every answer cites its sources.
The word that matters most is discovery. The agents are how it reaches a whole organisation, not the point of it.
Why it needs a name of its own
We tried describing this with existing words, and none of them held. A survey hears everyone but can't follow up. An interview programme follows up but only reaches a few. A readiness score tells you where you stand, not what to build. A roadmap tells you what to build, but rarely shows why.
Agentic discovery is a different shape of work: everyone heard, every finding traced, and a plan built from what the evidence supports. It changes what a leader can do with the result, and that's why we think it deserves a category of its own.
Three things that make it work
It starts by making honesty safe
People only tell the truth when they trust what it's for. If staff think discovery is a headcount review, they give safe answers, and a plan built on safe answers is a guess.
So Reccie is anonymous to your organisation: no one at your company sees who said what. Findings trace to roles, never to names, and what one person says is never repeated to another. Scout is always clearly AI.
Every build traces to a finding
Every finding links to where it came from. When someone corrects what was recorded, the correction outweighs what it corrects, and it's checked with others who work on the same part of the process.
A build is only proposed when the problem is confirmed by at least two more people, or shows up in more than one part of the process. When the evidence isn't there yet, we say so rather than force it. That's what evidence-led means in practice: a board can ask "why this, and why now?" and get an answer that points back to the people who do the work.
It ends in a blueprint, not a report
Understanding is only worth something when you can build on it. A discovery that ends in a report has failed the people who spoke up.
Agentic discovery ends in a build-ready blueprint. It maps the process step by step: who does each step, the systems behind it, the pain points and the time it takes. Then it ranks a first wave of builds against that map. The client owns the blueprint and chooses who builds from it. That can be any capable team, including 1QLabs.
Grow with the people you have
The point of all this isn't the agents. It's what the plan is for. We believe AI should amplify human judgement and grow what people can do, never replace them. When a plan is built from how the work really gets done, the first wave of builds gives the team more capacity and time back, so the business can grow with the people it has.
Where we go from here
We're early, and agentic discovery is a term we intend to earn rather than simply claim. We'll keep writing here about what we learn: how Scout earns candour, how Lens handles disagreement, and what makes a blueprint truly build-ready.
If you're working out where AI should go in your organisation, and you want a plan your board can check and your people will back, we'd like to hear from you at hello@1qlabs.ai.