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The FastEndpoints.Security package covers the token lifecycle end to end - creation with symmetric or RSA keys, an abstract refresh-token service that is secretly an endpoint, and a revocation middleware that makes you pay the lookup tax honestly. Part 8 of FastEndpoints in Depth.
The scariest agent mistake is not the invented method that errors on first run - it is the polished code that passes. Simon Willison's argument about hallucinations, and the four failure patterns I review for.
Nine parts of architecture posts lie by omission unless the tenth is the ledger. What earned its keep — isolation as data, MaxTenants = 1, the schema-keyed model cache — and the honest list of shortcuts: plaintext connection strings, cache windows, reflection, and a fan-out loop that still says TODO.
The Code-Review-Simplify loop has no natural end - an agent will polish forever if you let it. The four breakout constraints I arm around the loop, and how I match the exit to the risk of the work package.
KC Star's wishlist folder holds four future engines - a multi-engine measures platform, multi-tenancy, predictive monitoring, and automated maintenance - all marked research phase, one with 500 lines of not-ready reference SQL. An honest look at the roadmap, and which one I'd build first.
Execution is not one heroic pass - it is a three-step inner loop in which the agent codes, the output is read against the specification, and over-engineering is actively stripped out. The loop is my extension to the borrowed skeleton, and this is how it runs.
The complete honest ledger for a Key Vault-backed service discovery layer after years in production - the debts I would pay tomorrow, the trade-offs I would sign again, and the concrete signals that it is time to graduate to App Configuration, APIM, Dapr or a mesh. Part 8, the finale of Service Discovery Without a Service Mesh.
The Review phase is where a human takes an agent-graded plan and does the three things no score can - raise clarity, raise completion, minimise complexity - then encodes intent before a line of code exists. Why I call its exit the workflow's most important handoff.
Azure Blueprints driven from Terraform with forty templated parameters, platform-level delete locks, twelve-hour timeouts and PowerShell bookends on both sides of the apply - how the estate's most dangerous resource got its most governed deployment. Part 10 of the Terraform on Azure series.
PREVC's Planning phase has the agent decompose the work the way project managers always have, then do something no methodology asked of it - grade its own plan. The work breakdown structure, the fifteen-minute waterfall, and the three scores I added.
Pactify.AspNetCore in one sitting: an attribute, an assembly scan, and a /pacts/{provider} endpoint that serves your contract classes as live JSON - plus what a runtime contracts endpoint is really for.
KC Star V8's row-level trigger is genuinely selective. Its batch path, despite the name, loops every calculation-affecting dimension and recomputes most measures anyway. An honest audit of where the selectivity holds, where it doesn't, and a measure that zeroes itself out.
Agents now work unattended for stretches long enough that the conversation can no longer save you - why unstructured runs fail, the five-phase PREVC workflow I adapted from an open-source skeleton, and where this ten-part series goes.
The read side of archive-on-delete: querying archives through promoted typed columns, digging into jsonb payloads for everything else, polling snapshots with a 202 pattern, and an honest accounting of the restore path ArchiveKit doesn't have yet. Part 9 wraps up the Archive-on-Delete with ArchiveKit series.
The honest retrospective this series owes its readers - the thesis I believe but cannot cite, the threshold that is really one team's habit, the discipline with no how-to, the figures that will age, and the work you should not hand to an agent at all.
Where FeedR's data graduates from tick to fact: the aggregator's pricing handler, a second messaging seam with envelopes and metadata, Apache Pulsar as the durable tier, and the notifier's acknowledge-as-you-go consume loop. Part 7 of the FeedR deep dive.
Dan Shapiro's Five Levels ladder maps where the industry actually stands with autonomous coding agents - most of it lower than it believes - and StrongDM's three-person software factory shows what the top rung looks like when someone builds it.
KC Star V7 ships two overlapping ways to partition and age out cold data - a static backup-partitioning subsystem and a dynamic one - both monthly range partitions on CreatedDate, both gated on one flag. The honest read on why a feature ended up implemented twice.
The retrospective, with the ledger totalled - seven byte-identical MessageBrokers, one AggregateRoot with three meanings, what Convey genuinely optimises, where a Convey.Bootstrap meta-layer should have stood, and what a consumer should copy from this estate.
The disciplines tell you what to learn - the primitives are what you actually write. Five small, recurring artefacts of AI-directed work, from the self-contained problem statement to the evaluation harness, each shown with a worked example.
Delete your controllers and Swashbuckle goes blind. Convey rebuilds the OpenAPI document by hand from its endpoint registry - a document filter, a naming convention, and a few spec violations it hopes you won't notice.
Two fix scripts in KC Star repair a V6 database where dimensions were hand-seeded but the fact-generation half of the pipeline never ran. A war story about half-run pipelines, the DO-block backfills that rescue them, and what a MANUAL_SETUP batch id confesses.
Redis registered in nine services and read in one, discovery stacks in services that never call anyone, an outbox package referenced but never wired, and versions that float by construction - an inventory of everything Pacco wires up and never uses.
The highest-leverage discipline in the stack is writing down what done looks like - what a specification must contain before an agent can execute for hours against it, and what Addy Osmani's 80% problem actually says about the work that remains.
Archive tables are meant to empty out - a background worker migrates their rows into the current table while live traffic reads and write-through updates race it. This part walks the EF backfill's insert-then-conditional-delete choreography and the timestamp that keeps it honest. Part 9 of the Entity Versioning with VersionKit series.
