Agent and workflow pipelines
Multi step processes where a model calls real tools against real systems, built so a failure halfway through does not leave your data in pieces.
The problem
Agent demos are easy. Agents that touch a production database, retry safely and can be replayed after an incident are a different discipline.
What the work involves
- Explicit state machines rather than hoping the model remembers the plan
- Idempotent tool calls, so a retry cannot double charge or double send
- Human approval gates on anything irreversible
- Full execution traces, replayable after the fact
- Budget and step ceilings, so a loop cannot run up a bill overnight
Typical stack
MCP
Temporal
Laravel Queues
Celery
Redis
Python
TypeScript
Indicative rather than fixed. The right choice depends on what you already run, and inheriting a stack your team knows usually beats introducing a better one nobody can maintain.
Got a agent pipelines problem?
Technical detail welcome. The more concrete the problem, the more useful the first reply.