← The ADLC library
Platform economics & tooling
A desk of the Fastpace GroundTruth library
What this actually costs, and what it is worth.
The money: per-ticket agent cost, attributing model spend, cost controls that do not quietly degrade quality, build versus buy on the control layer, and the honest version of measuring return without flattering the numbers.
Economics & toolingThe long view 23 articles
Articles
- Your test suite now certifies the bug When the same interpretation produces the code and the tests, a wrong assumption does not just slip through. It gets a regression guard, a CI budget and a permanent defender. That is a liability with a recurring cost, and almost nobody accounts for it.
- Against the AI debt panic A remediation market is being sold before most buyers have measured the problem. The panic buys the wrong thing: an audit produces a report, and a report is not the deliverable you need. The fix is a rate control you already own.
- Consistency stopped being a preference Arguments about doing things one way used to be about taste, with a modest payoff in onboarding. Consistency is now a metered input cost, paid on every generation and every review, and the economics of the argument have completely inverted.
- The refactor that pays for itself thirty times The value of a refactor was always the saving per future touch multiplied by the number of future touches. Agents did not change the saving. They changed the multiplier, and that turns a small number of cleanups from indulgence into obvious spending.
- Craft when typing is free Craft has always been defended on moral grounds, and that argument loses every budget meeting. When generation costs almost nothing, the case for craft becomes a cost case, and it is much stronger than the aesthetic one ever was.
- Sixty-one billion workdays is a number that means nothing Global technical debt estimates size a market. They cannot justify a single decision in your organisation, and a budget request built on one gets funded once and cancelled twice.
- Delete more than you think you can Writing code got cheap. Deleting it did not, and its value went up. Deletion is now the highest-return operation in a codebase and the one your organisation rewards least.
- Generated code is maintainable. Unread code is not. The claim that AI writes unmaintainable code confuses a property of an artefact with a relationship between an artefact and a reader. Maintainability was never in the file.
- Comprehension debt is worse than code debt Code debt makes change expensive. Comprehension debt makes change unsafe, and the real cost is not the hours you spend but the changes you quietly stop attempting.
- The remediation market is coming. Do not be its customer. Gartner expects a market for auditing and refactoring AI-generated debt. The category will exist and it will be well funded. Most of what it sells is priced against a symptom by vendors with no reason to remove it.
- When the agent is cheaper than the meeting about the ticket Software economics has always been discussed in terms of engineering time, which was the expensive input. Once generation is nearly free, the expensive input turns out to be coordination, and almost nothing in how we work is organised around that.
- Measuring ROI without lying to yourself Almost every published productivity figure for agentic development is measuring something easy in place of something that matters. Here is what the honest version looks like, including the parts that are uncomfortable.
- AI-generated technical debt deserves its own category The debt everyone is worried about is not worse code. It is code that works, that nobody has read, in quantities no team can catch up on. That is a different problem with a different fix.
- Model choice as an economic decision Teams pick models the way people pick text editors, on affinity and habit. It is a routing problem with a measurable answer, and the answer is different for different kinds of work in the same codebase.
- Build versus buy for the ADLC control layer This decision gets made badly in a specific and repeatable way: teams estimate the demo and pay for the maintenance. Here is what the real comparison looks like once you count the parts nobody demos.
- The hidden cost of context Every conversation about agent economics focuses on output tokens, which are the visible half of a bill dominated by the invisible half. Context is the line item nobody budgets and almost everybody overpays.
- The ADLC in five years, and what stays human The generation of code is nearly solved. Taste, judgement about what is worth building, and the person who answers when an agent is wrong are not, and will not be.
- Attributing model spend to features and teams Splitting one provider invoice across an org chart looks like an accounting problem. It is really a question about where you draw the boundary, and the boundary you pick changes behaviour.
- Cost controls that do not degrade quality Most cost controls are quality cuts in disguise, and the bill just moves to a line item nobody is watching. A few are free. Here is how to tell them apart.
- The parts of this that get more expensive the longer you wait Most of what you will need for an agentic organisation can be added the day you need it. Two things cannot, and they are the two everybody defers. Here is why the order matters more than the timing.
- What we will miss about the SDLC Every transition in this industry gets narrated by its beneficiaries, which means the losses go unrecorded until it is too late to keep any of them. Some of what the old life cycle provided was genuinely good.
- Predictions we are willing to be wrong about Seven claims about where the ADLC goes next, each with a date and a stated condition that would prove it wrong. A prediction nobody can check is not a prediction.
- What agents actually cost, per ticket Your provider invoice is a single number for a hundred different activities. Here is how to build a per-ticket cost model that survives the next price change.
The other desks
Delivery & program intelligenceWhat the numbers do when agents arrive. Engineering leadershipWhat happens to the people when the code writes itself. Governance, security & complianceThe questions an auditor will ask, before they ask them. Product & acceptance criteriaDone, defined precisely enough that a machine can check it.