The Future of Coding Is Orchestration

As CTO at Ciridae, I used to measure momentum in keystrokes—lines added, diffs merged, tickets closed. That framing breaks down when the fastest path to production isn’t typing; it’s arranging. The future of coding is orchestration: specify the outcome, define contracts and invariants, and let the system assemble the pieces. Claude Code is the first tool that made that shift stick across our entire engineering org.

The receipts-by-SMS project was the proof point. Field workers text photos of receipts; we return structured invoices without manual entry. The components are standard: a programmable SMS gateway sends webhooks, Temporal provides fault-tolerant workflows and state, an AI image parser extracts line items, and a record-management API updates invoices. The slow part used to be glue: endpoint contracts, parsers, error paths, policies around retries and alerts. Claude Code handled the connective tissue and the boring fragility, documentation drift, auth quirks, client scaffolding, so the first iteration behaved like our codebase, not a demo. Most importantly, test failures weren’t dead ends; Claude read the logs, adjusted the parser and orchestration, and moved forward.

Precision was the unlock. The more concrete the spec, file names, method signatures, payload shapes, return types, the more the system behaved like a teammate who knew our preferences. Writing “create a parseReceipt.ts module with parseLineItems(buffer): { items, subtotal, tax, total }, add three fixtures, and ensure the Temporal activity retries on network timeouts only” produced code that dropped straight into review. Ambiguity wastes cycles; orchestration rewards specificity.

To keep that specificity stable, we introduced a CLAUDE.md at the root of each repo: brief project overview, directory structure, naming conventions, invariants, testing strategy, and the handful of decisions we don’t want to re-argue. Because Claude Code treats this as first-class context, new sessions begin aligned with our architecture. That single page shortened onboarding for the tool and for humans. It also made parallelism safe: I often run three or four instances at once across repos without losing consistency.

We’re Anthropic preferred partners, and we now run Claude Code at enterprise scale across our workflows. The gains show up in day-to-day engineering rather than a single flashy demo. Context management happens automatically; we don’t babysit file lists. Refactors that used to require a day of careful renaming and validation land with the right migrations and checks. Merge conflicts resolve the way we would resolve them. Pull requests arrive with rationale, test diffs, and notes for release. Routine implementation—clients, serialization, fixtures—stops blocking design decisions. And the parallel work streams don’t step on each other because the orchestration is explicit.

On my productive days, I have like three or four Claude Code instances running simultaneously on different projects. Sometimes I’ll spin up a branch for a ticket, let Claude Code take a first attempt, and when I come back it’s like a junior engineer already made a draft implementation. I haven’t written a pull request manually since I started using it

CYRUS SINGER
Founding Engineer

Our development loop changed accordingly. We write tests and expected outputs first, then ask Claude Code to generate the implementation and the tests that exercise the behavior. Review shifts from syntax to systems: are we honoring invariants, are the workflows idempotent, are retries bounded and observable, is the logging structured for production debugging? CI becomes a feedback channel, not a gate. When something fails, Claude reads why and adjusts

the orchestration rather than papering over symptoms. The cycle is short: specify, generate, review, iterate, merge.

Why now? A few primitives finally matured together. Claude Code’s context handling means we specify intent instead of curating files. Repo-aware operations turn instructions into deterministic edits, not suggestions. Tight loops with tests and logs make failure data useful in the moment. A lightweight memory (CLAUDE.md) carries design decisions forward so each branch starts smart. And the enterprise pieces—permissioning, audit trails, predictable diffs—make the tool viable beyond hobby projects. Put together, this is less “autocomplete” and more “continuous delivery for decisions.”

The same pattern helped us integrate legacy systems that used to demand hours of archaeology. A brittle API stops being a research project and becomes an orchestration problem: define the boundary, encode the contract, isolate side effects, name failures, and let the workflow enforce the rules. The implementation matters, but the orchestration makes it durable.

If yesterday’s AI story was speed—prompt, code, ship—today’s story is arrangement. The work that moves the needle is deciding how services talk, how failure behaves, and how knowledge persists. Claude Code didn’t make us type faster; it made us specify better. That’s the practical meaning of “the future of coding is orchestration,” and the reason the answer is “why now.”