In two days from AI use case to a production-ready decision – on the real backlog, the real architecture and, where cleared, the real code.
Thirty minutes with an operator. Then you get scope and a fixed price.
Run by Simon Scheurer and Marc Gasser – in person, start to finish.
More generated code is not a product outcome. Without solid problem evidence, AI-ready data, quality gates and an operating plan, AI may be accelerating the wrong part of the system.
In the AI Monitor, usage sits at 66 out of 100. The organisational groundwork beneath it sits at 50. People moved faster than data, integration and governance.
Clear which use cases get built now, tested first, deferred or stopped. One of them is specified production-ready.
Product and tech red-flag map
Five working days after the intake, the team has the red-flag map – with the three biggest uncertainties for the decision sprint.
Pick an archetype and rate four dimensions. The verdict appears immediately – with the criteria that produced it.
AI Use-Case Decision Snapshot
Basis: 162 valid responses, 106 of them with demographic detail. AI Monitor 2026, published by Teklens with ETH Zurich and the University of St. Gallen. Self-assessments, normalised to 0–100. Pre-release.
Every component names the obstacle it removes, the artefact you receive and when it is delivered.
We work on the real backlog and the relevant technical material.
Signals, decisions and technical reality sit apart
A shared baseline from backlog, architecture, data and code context
before the lab
Ideas get built before value and feasibility are settled
Facilitated assessment by impact, feasibility, evidence and risk
day 1
Use cases can't be steered as a portfolio
3–5 prioritised use cases marked NOW, EXPERIMENT, LATER or NEVER
day 1
A use case is strategically attractive but not described so it can ship
Problem, users, data, architecture, evaluation, failure modes and scope
day 2
Unclear production readiness
Five gates for value, data, reliability, security and governance, and operations
day 2
No clear sequence after the lab
Projects, owners, kill criteria, metrics and review points
within five working days of the lab
Decisions and product evidence get lost
A versioned workspace for signals, use cases, architecture, delivery and operations
with the roadmap
Templates created during the lab that your team keeps using afterwards. We don't attach invented individual values to them.
6-Week AI Product Shipping Sprint
The Decision Lab plus six weeks of execution on the prioritised work – in small batches, with review and evaluation.
We don't promise «two shipped features» as a blanket commitment. What ships in six weeks depends on scope and technical dependencies – we settle both in Decode before committing to anything.
AI usage runs ahead of the groundwork beneath it: data, integration, governance and the ability to adapt.
of AI projects will be abandoned through 2026 for lack of AI-ready data.
That is how much slower experienced open-source developers were with AI tools – while feeling faster.
The method from research, the cases from practice. What we apply in the labs is tested against both.
ETH Zurich and the University of St. Gallen are research partners on the AI Monitor. They are not Teklens reference customers.
Anonymised example · B2B SaaS, around 40 engineers
| Gate | Criterion | Status | Owner |
|---|---|---|---|
| Value | Metric defined and measured today | Met | PM |
| Data | Coverage, freshness and provenance settled | Open | Data eng |
| Reliability | Evaluation set and error budget in place | Met | Tech lead |
| Security | Data residency, roles and logging settled | Met | CISO |
| Operations | Monitoring, cost and rollback defined | Open | Platform |
What we have delivered. Where nothing is cleared yet, a clearly labelled anonymised example.
No junior with a slide deck, no partner who disappears after the kickoff. Simon Scheurer and Marc Gasser run every lab themselves – the same two people from the first question to the decision.
Technology, product and engineering teams
Go-to-market, revenue and automation
Both are co-founders of Teklens, working out of Zurich. Labs run in German or English.
Two options, one scope. The Execution Track sits first because it shows the full extent – the recommended entry is the Decision Lab.
Diagnosis, a shared decision and a concrete execution plan. For teams that need clarity before they commit capital or capacity.
The scope is set; the price is fixed in the scoping call and confirmed in writing. No line items appearing later.
When the agreed inputs are complete, we deliver the defined Decision Pack by the agreed date. If an agreed component is missing, we keep working at no extra fee until the pack is complete.
Clear which use cases get built now, tested first, deferred or stopped. One of them is specified production-ready.
Review a use case with an operatorThe Decision Lab plus real execution, reviews and embedding into how the team works.
The scope is set; the price is fixed in the scoping call and confirmed in writing. No line items appearing later.
When the agreed inputs are complete, we deliver the defined Decision Pack by the agreed date. If an agreed component is missing, we keep working at no extra fee until the pack is complete.
Clear which use cases get built now, tested first, deferred or stopped. One of them is specified production-ready.
Review a use case with an operatorWhen the agreed inputs are complete, we deliver the defined Decision Pack by the agreed date. If an agreed component is missing, we keep working at no extra fee until the pack is complete.
We guarantee defined outputs and dates that we control. No revenue, transformation or autonomy guarantee – that depends on your execution, and we can't stand behind it.
After Decode and Shape, you decide – not us.
The Execution Track does not start automatically. A reasoned wait or stop is a valid result – and often the most valuable one.
The evidence holds. We start the Execution Track.
A bounded test resolves the open uncertainty before capacity is committed.
Fix the groundwork or the input first. With a criterion and a review date, not as a postponement.
No sensible business case. Recording that with reasons saves more than any pilot.
A loop, not a transformation with an end date.
Understand reality, context and the bottleneck
Where do we actually stand?
Set decisions, priorities and limits
What do we change – and what don't we?
Turn decisions into real work
How does measurable impact happen?
Embed learning, governance and routine
How does the system get better?
The Decision Lab covers Decode and Shape and hands over to Amplify and Evolve. The Execution Track runs the whole loop.
Every lab leaves behind a versioned Context Workspace: evidence, decisions, work, rules and what you learned, in one place. Human-readable, machine-readable for approved agents, exportable.
/product-ai/
00_customer_context/
01_opportunities/
02_use_cases/
03_architecture_data/
04_delivery/
05_operate/
06_roadmap/The cycle we work through in the lab is the same one Teklens works along: discover, define, build, operate. Where Teklens takes the work off your hands, we show it on our own repo. Where you're better off solving it without a tool, we say that too.
No. It settles what should be built at all. More generated code is not a product outcome – automate bad input and you just ship the mess faster.
That's precisely the finding: in the AI Monitor usage sits at 66 out of 100 while the groundwork beneath it sits at 50. The lab works on the groundwork, not on usage.
No. Code access is optional and only if you clear it. Hosting in Switzerland and the EU, no training on your data, model choice per project.
Then that's a result. A reasoned later or never saves more than a pilot that gets quietly shelved after nine months.
No. What's assumed is product and engineering experience, not AI experience.
No, and we deliberately don't promise it. What ships in six weeks depends on scope and technical dependencies. We settle both in Decode – only then do we commit.
Thirty minutes with the founding team. You get a clear recommendation, the right scope – or a reasoned no.