AI speeds up the wrong stretch
Writing code gets faster; deciding what to build and checking it works does not. The bottleneck moves, it doesn't disappear, and the debt grows.
For software and SaaS companies
Your team has AI copilots. And it moves just as slowly as before.
It isn't the tool. With your team we build two things that stay with you: the context the AI works in and the process you work with.
Why it stalls: in a software company it's almost always this
You already have good engineers and AI tools. If speed doesn't go up, it's rarely a problem of talent or licences.
AI doesn't know your product
Without your rules, your architecture and your product knowledge, the AI answers in generic terms: it works in the demo and breaks on the real case.
Nobody decides where a person signs off
Without a clear process, either everything is approved, which is a jam, or nothing is reviewed, which is debt. What is missing is deciding where the risk is and who signs off there.
How we do it
Two things that stay in your team: the context and the process
We work with a pilot team, on their real code and without stopping their deliveries.
The context
The context the AI works in
The house rules, product knowledge, specialised agents for each phase and automated checks: everything the AI needs to know and respect to work well on your project. In practice, context engineering.
The process
The ten-step process
From the idea to updated documentation, with Spec-Driven Development: the specification, not the generated code, is the source of truth. In four of the ten steps a person decides.
A person decides where there is risk. Your team keeps the context and the process, and grows them with every project.
See the detail of AI-Accelerated Development
The technical detail: context engineering vs. prompt engineering.
Results
What changes when the context and the process are right
Results of the method in product teams; the ×8 comes from a B2B SaaS case.
×8
Functionality delivered per sprint
0
Lost sprints while rolling out the method
−50%
Time-to-production
Every team starts from a different place: in the diagnostic we set the delivery and quality baseline and compare it at the end. We don't promise a number before measuring.
Cases from product companies
The same method applied to software companies and digital product.
Product team · AI development
A product team that kept missing deadlines adopts AI with a method: Spec-Driven Development, Scrum and CI/CD
Transforming a product team towards AI-native development
- Functionality delivered per sprint
- ×8
- We introduced the method without pausing delivery
- 0
Full development
From idea to production MVP: Plannet connects communities through events
A complete social platform to create, discover and manage local events and plans
- From concept to app in the stores
- 12 weeks
- Scalable and serverless with AWS
- 100% Cloud Native
Full development
Hacktua: a wellbeing app with 380+ pieces of content and a personalized profiling algorithm
End-to-end development of an iOS/Android mobile app with CMS, learning paths, recipes and cross-platform subscriptions
- Users generated around the platform
- 86,100
- Apple Store and Google Play
- 5.0★ / 4.9★
Guides for software and SaaS companies
What we have learned taking AI to production in product companies.
An AI agent in your SaaS product: build the team or bring in a partner?
Read article
Integrating AI into your SaaS product without mortgaging the roadmap
Read article
How to know if your product's AI works: evals and cost
Read article
Claude vs Cursor vs Copilot for enterprises: which to choose
Read article
AI-accelerated dual-track Scrum: how to implement it in your team
Read article
Context engineering vs. prompt engineering
Read articleFrequently asked questions
Frequently asked questions
How does AI apply to a software or SaaS company?
On two fronts. Inside: accelerating your development team to deliver faster without piling up debt, with the right context and process and not just licences. And in your product: putting AI —RAG, agents, LLM features— in so that it reaches production with cost and quality under control. In both cases the point is not the tool: it is that the AI knows your business and that a person decides where there is risk.
Why does my product team have AI copilots and not go any faster?
Because AI speeds up writing code, which is rarely the bottleneck. The jam is in deciding what to build and checking that it works. If AI generates faster without a specification or checks, you multiply speed and debt at the same time. The problem isn't Copilot or Cursor: it's the context and process around them.
How do I put AI (RAG, agents) into my product without mortgaging the roadmap?
With context engineering and a person who decides where there is risk: gather how your product and your business work, turn it into the context the AI uses, and take each feature to production with the cost measured from day one. That way the AI in your product is consistent and auditable, and you don't stop the roadmap to get there.
Do we have to stop shipping?
No. The Quick-start works with a single pilot team and on real work you had already planned, in parallel with its sprint. There is no need to pause deliveries.
What results have you achieved at software companies?
Three real examples: a B2B SaaS product team went from missing deadlines to ×8 functionality delivered per sprint and 0 lost sprints; Plannet took its social MVP to production in 12 weeks, 100% cloud-native; and Hacktua built an app with 380+ pieces of content and a profiling algorithm, with 86,100 users and 5.0★ / 4.9★. Each case has its own page with the detail.
See where your team stands
Answer 16 questions about how your team works with AI today. It is free.
Start the self-assessment- questions
- 16
- blocks
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Contact
Let's talk about your team and your product
A free, no-commitment diagnosis: a conversation to see where your team is stalling and what it would take for AI to make you ship faster, without stopping your deliveries.
What happens next
- You write to us. Two lines are enough.
- We reply within 24 working hours and set up a call.
- On the call we tell you whether we can help and where to start.
Tell us what you want to solve
Tell us who you are and what you need.