LLM as Navigator (Not Oracle)
The stance that an LLM is best used to guide you toward an answer — orienting, locating, and explaining — rather than trusted to deliver the final answer itself.
Also known as: help navigate the way to the answer, navigate to the crucial parts of the code, LLM as navigator, navigator not oracle
Part of: LLM Limitations
Documents (2)
- Expedia Uses AI Driven Service Telemetry Analyzer to Accelerate Incident Investigation Leela Kumili · 2026-07-23 source ↗ Reader 🖥️
Expedia built STAR, an internal AI-assisted observability tool, on the premise that a deterministic, human-validated, prompt-chained workflow over standardized infrastructure telemetry -- deliberately forgoing function calling, RAG, memory and autonomous tool use -- is the right way to accelerate production-incident root-cause investigation today, with engineers remaining the final validators of every finding. - Fragments: February 4 Martin Fowler · 2026-02-04 source ↗ Reader 🖥️
AI is reshaping the developer's relationship to understanding: it can erode comprehension of the systems we build, is wisely used to navigate toward an answer but never trusted for the answer itself, and may make code cheap enough that the specification becomes the durable engineering artifact.
Propositions touching this concept (1)
By publication month, oldest first (extraction month when no publication date is known).
2026-02
- explicitFully trusting the answer an LLM gives you is foolish, but using an LLM to help navigate the way to the answer is wise.
Tensions
Is code a durable artifact to be maintained, or an ephemeral byproduct regenerated from a more durable source (spec/objective)?
from: What is the future of software development in the agentic/AI age?
- We've Stopped Arguing About Whether AI Changes Software (Greg Herlein): Code is (or is becoming) ephemeral — a disposable byproduct the agent regenerates from the spec; the spec is 'the point.'
- Fragments: February 4 (Martin Fowler (Feb 4)): When coding is free, the specification-plus-tests becomes the durable, primary engineering artifact.
- Software Design in the Agentic Age: Place Your Bets (Mathias Verraes): Specifications could replace code as the source of truth, but throwaway regeneration is a bet he is unwilling to make; keep code durable and revertible.
- Why did Martin Fowler invite 60 engineers to a ski resort? (Ivett Ördög): Code endures because the winning agents behave like engineers moulding a maintained codebase, not compilers regenerating from scratch.
- What Survived Contact (Sam Ruby): The durability question is a category error — what endures is neither the code nor the prose spec but the objective and its oracle.
Assessment: The most-cited open question of the corpus, and genuinely unresolved (Herlein: 'no consensus here. None.'). The 'code is the better spec' counter is strong — code is unambiguous, executable, deterministic, whereas a prose spec is reinterpreted each run, which sits in tension with verifiability being the quality bar. Ruby's move is the most defensible: it dissolves the code-vs-spec fight by locating durability in the evaluation rather than any representation. Verraes and Ördög expose the load-bearing empirical unknown — nobody has data on regenerate-vs-patch cost or on long-term evolvability of agent-maintained code.
Is preserving human understanding of the system a first-order value, or is comprehension safely offloadable so long as output is verifiable?
from: What is the future of software development in the agentic/AI age?
- Fragments: February 4 (Martin Fowler (Feb 4)): Preserve understanding: it is a first-order value, and practices that force explanation defend it.
- Fragments: February 9 (Martin Fowler (Feb 9)): Preserve understanding and craft: cognitive debt and the loss of model-building are the real costs to guard against.
- Jimmy Nilsson's Post — reflections after the Thoughtworks 'Future of Software Development' retreat (Jimmy Nilsson): Preserve the human: 'Extreme Humanism' and being conspicuously human are load-bearing anchors.
- We've Stopped Arguing About Whether AI Changes Software (Greg Herlein): Offloadable: the quality bar is 'is it verifiable enough,' not whether a human read or understood the code.
- Looking back at the Future of Software Engineering unconference (Bartosz Ocytko): Offloadable for most builders: citizen developers need never read the code if a constrained platform makes failure modes disappear.
Assessment: The optimist-practitioner vs. skeptic-humanist axis. Fowler and Nilsson treat comprehension and craft as intrinsic goods whose loss is a harm even when output is fine; Herlein and Ocytko treat comprehension as instrumental — replaceable by verification and platform guardrails. The humanist camp has the stronger long-run argument (Fowler's cognitive-debt case and Ocytko's own 'who-guards-the-guards' problem both show verification and guardrails are themselves fallible artifacts that someone must understand), but the offloadable camp is describing what is actually happening at scale. The crux is whether verifiability can ever be robust enough to make understanding optional — which Ruby's own Goodhart gap (a passable oracle diverging from true intent) suggests it cannot fully be.
Open gaps (1)
- uninformedNo detail is given on how the 'domain-specific prompts' are engineered, what mitigations exist against LLM hallucination or fabricated root causes in the multi-stage summarization, or what the SME-review/Langfuse evaluation loop actually measures (accuracy? usefulness? both?). The article names the ingredients (Langfuse for prompt management/tracing/evaluation, SME review, user feedback) without describing evaluation criteria or results.Expedia Uses AI Driven Service Telemetry Analyzer to Accelerate Incident Investigation — read next: Read Expedia's original Medium engineering post (linked in the article) for evaluation methodology details, or look for a follow-up on false-positive/false-negative rates in STAR's generated findings.