Delivery Playbook · Start here
Principles
Our four values, and the six working rules that put them into practice.
We behave, manage, and are guided by our core values: Kindness. Sustainability. One-Team. Excellence. They are not slogans on a wall. Each one shows up as specific habits in how we plan, build, review and report. Below, you will find each value as TechSoft defines it, with what it looks like in delivery, followed by the six working rules that put the values into practice.
Our four values
#Kindness
We treat other people the way we want to be treated by being honest, transparent, respecting, caring, guiding, supporting, and cheering each other. In delivery: We listen before we propose, in interviews and workshops; Retrospectives look at how we work, not who to blame; Bad news and risks are shared early, with options attached; Code review is about the code, and it is always polite.
#Sustainability
We aim for a healthy and long-term journey by first being healthy, constantly learning and growing, and sharing knowledge with our team and the community. In delivery: A steady one-week rhythm, so the pace can continue; Every change is understood by an engineer before it ships; Runbooks and documentation are part of the work; Small, reversible releases instead of big risky ones.
#One-Team
We are united and highly committed for team results by taking ownership of our assigned tasks in proactively finding creative ways to success, obtained from collective results. In delivery: The customer's product owner takes part in planning and review; Design, QA and DevOps sit in the team from day one; One backlog and one board that everyone can see; Every activity has one role that answers for it.
#Excellence
We aim to deliver WOW results with a focus on quality, by keeping our commitment to making a bit better progress every day. In delivery: A clear definition of done, with no "almost done"; Four quality gates between an idea and production; Tests, security checks and review on every change; Results measured against a baseline recorded at the start.
Six working rules
A playbook is only useful if people follow it when it is inconvenient. These rules settle the tie: when two good options conflict, the team picks the one that fits them better.
1. Outcomes before output · #Excellence
We agree what success looks like, measured against a baseline, before we write code. A feature that ships but does not move the outcome is not a success.
2. One team with the customer · #One-Team
Customer and TechSoft roles are clear. The customer's product owner is part of the team, not a reviewer at the end.
3. Small increments, visible progress · #Sustainability
We release often, demonstrate working software and prefer many small, reversible steps over one large, risky one.
4. AI speeds us up, people own the result · #Sustainability
AI is part of the workflow. Every change is understood, reviewed and owned by a named engineer.
5. Quality is built in · #Excellence
Tests, security checks and review are part of each change, not a phase at the end.
6. Honest reporting · #Kindness
Risks, trade-offs and open issues are shared early, including when they are uncomfortable.
How the rules show up day to day
| Working rule | In practice | Where to read more |
|---|---|---|
| Outcomes before output | Success measures and baseline recorded in Discover; reviewed monthly | Discover · Metrics & reporting |
| One team with the customer | Customer product owner in planning and review; shared backlog | Cadence & meetings · Decision rights |
| Small increments | Sprint demos; releases behind rollback plans | Build · Quality gates |
| AI speeds us up, people own the result | AI-use policy; mandatory human review | AI-assisted engineering |
| Quality is built in | Definition of done; automated gates in the pipeline | Definition of ready & done · Quality gates |
| Honest reporting | Weekly status with risks; escalation path | Escalation & risk |
Related
Start here
How the team is organized
The customer and TechSoft roles that make up an engagement, and how they connect.
Quality & AI
AI-assisted engineering
Where we use AI, the rules that keep it safe, and who is responsible.
Quality & AI
Quality gates
Four gates a change passes between idea and production, and what each one checks.
