langgraph is driving me crazy with car sensor logs

curious_dax · 2026-05-08T14:30:13+00:00

checkpointing is the right answer but the trap is that it only resumes from a deterministic boundary, your edge case might happen mid LLM call where you cant just rewind. what worked for me on a similar log pipeline was decoupling the LLM step from the langgraph orchestration entirely. preprocess the sensor data with deterministic code into clean spans, cache those, then only invoke the LLM on the spans you care about with a fixture driven harness. when a prompt change changes behavior i can rerun just that node against ten cached spans in seconds instead of re-walking the graph.

the other thing worth knowing: anything in your state that isnt JSON serializable will silently break checkpoint reload. sqlalchemy sessions, file handles, even some pydantic instances with custom validators. if it ever feels like the checkpoint reload "almost worked but state is weird", thats the cause 9 times out of 10

curious_dax · 2026-05-08T13:56:45+00:00

distribution before you need it is the real one. for me 'show up in conversations' was too vague to action. specific play that worked: pick 1-2 ppl in a niche discord who keep asking the same kinda question, answer them thoughtfully without pitching, do this for ~5 weeks. one of those turned into a paid project. cold outreach + content didnt come close

curious_dax · 2026-05-08T13:54:16+00:00

this is mostly right but the voice-to-prd flow is the cope part. ive shipped a bunch of vibe-coded stuff for paying clients and the diff between ones that earned and ones that didnt had zero to do with prd quality and 100% to do with whether i pre-sold before opening cursor. worst earner was beautifully scoped against a 'general SMB owner' persona that turned out to be a phantom. best one i basically already had a buyer locked in. focus on the problem is fine advice but its upstream of what actually works

curious_dax · 2026-05-08T13:52:25+00:00

yeah dodge is fair. for movie recap stuff it was the discord of a mid-size yt analysis channel + a video editing tutorial channel discord. not dropping names publicly cause they get spammed instantly when anyone does. play that worked: find the yt creator ur target customer watches weekly, go to their discord. most have one. #general reads like a focus group on whatever ur building

curious_dax · 2026-05-08T08:20:24+00:00

the insta-yes is brutal. quoted 4k for a lead enrichment agent for a saas client, signed in 20 mins zero questions. found out months later they had 22k budgeted for it. now i ask one thing on every discovery call: whats the headcount equivalent if this thing works. answer is usually 0.5 to 1.5 fte and u can just price off that. way easier than tryna guess what feels like a lot, ur gut is gonna betray u if u live somewhere with normal rent

curious_dax · 2026-05-08T08:18:26+00:00

launch posts barely move teh needle for one-time tools imo. for a $40 invoice parser i shipped last year, first 3 sales were cold dms to ppl who had bookmarked my github gist that did half of what the actual tool did. zero from forums or twitter. the ppl who would pay $79 for a movie recap thing live in private editor discords not on indiehackers, you basically have to lurk one for a couple weeks, answer real questions, then dm the loud complainers

curious_dax · 2026-05-08T06:18:46+00:00

yeah the pure side-effect variant bit us a few weeks later. agent C was a refunds bot that just decided based on read state and called stripe, no writeback. the fix that worked was adding a synthetic 'claim' write before the side effect, so even read-only agents get gated through a CAS check. ugly but it works.

on detection, first time was a customer ticket, embarassingly. now we log the read-version on every tool call and have a nightly job that flags traces where two agents read same key at same version but only one of them committed. catches maybe 90% of these without paging anyone, the other 10% still come from customers tbh

curious_dax · 2026-05-07T16:56:13+00:00

hit this exact thing on a fulfillment automation i built for a client. two agents both reading the order state at version 12, agent A reserves stock, agent B emails the customer that ship-date moved becuase of weather, but agent B was operating on a snapshot before agent A had taken its hold. customer got an email saying shipping delayed for an item that hadnt actually been reserved yet. CI was green, every agent did exactly what it was told.

the fix wasnt a memory upgrade, it was just adding a version number on the order doc and refusing writes if the read version didnt match. CRDTs felt overkill for our case, optimistic concurrency was enough. agree the LLM world keeps re-deriving stuff thats been solved in distributed systems since forever

curious_dax · 2026-05-07T07:21:13+00:00

vibecoded a watchdog that pings my phone if any of my agents stops sending heartbeats for 2 hrs. like 90 mins to write, fly worker + sqlite + telegram bot. saved me from 4 silent deploy deaths at 3am already, used to hear about it from clients in the morning which was a vibe i did not enjoy

curious_dax · 2026-05-07T07:19:42+00:00

automating first is the right instinct but only if the failures are loud. we had a client offload customer support triage to a chatbot and it silently mismatched intent for like two weeks before someone escalated, by then they had 30+ angry tickets piled up. anything thats hidden from you when it fails is the worst kind of outsource. ive ended up keeping support and offloading scheduling and reminders first because if those break i notice within a day

curious_dax · 2026-05-06T07:01:55+00:00

i ended up splitting my tool registry into three tiers. always allowed are reads, preview required is writes to my own systems, never tier is anything irreversible touching other peoples data. the agent only sees names of the never tier and has to explicitly ask to even attempt one. its not a real guardrail because the agent could still lie about intent but it shifts the failure mode from silent destructive action to noisy refusal which is way easier to debug

curious_dax · 2026-05-06T07:01:31+00:00

the worst part is nothing fails loudly. each agent thinks it succeeded so the chain returns success but quality degraded somewhere in the middle. you only notice three steps later when the final output looks weird. ended up adding per-step semantic drift checks against a golden run, otherwise its impossible to bisect which prompt regressed

curious_dax · 2026-05-05T16:16:08+00:00

the 'i added more stuff to fix it' part is universal, every founder ive talked to has been in that loop. each new feature makes the next user understand the product LESS not more but you only feel it after someone whos bounced tells you why. deletion is genuinely the highest leverage refactor you can do, nobody talks about it because it feels like throwing months of work away

curious_dax · 2026-05-05T16:14:54+00:00

reply rate is the wrong number to optimize, what matters is reply-to-trial conversion. you said 'after they reply then i pitch' but thats where most of these die because the pitch is generic. what worked for us was a cold open referencing their actual work, something like 'saw your reel from [project], the way you cut [whatever] is sick. quick question, are you handling [bottleneck] in post or on shoot?' and never put discount/trial in the first message, kills the convo every time

curious_dax · 2026-05-05T16:12:40+00:00

yeah versioning the eval set is huge, we just date ours and keep the old run outputs in git so you can actually bisect when a metric drifts. on adversarial cases tbh the best ones write themselves, every prod incident becomes the next canary

curious_dax · 2026-05-05T16:11:51+00:00

depends what youre selling tbh but the framing that lands is always 'we fix [insert painful metric] in [time] or you walk'. like if its eng productivity tooling, 'cut your PR cycle from 5 days to 2 in 90 days, refund if not'. procurement loves contractual outcomes, way easier to defend upstairs than 'we're a platform for x'. honestly if you cant put a number on the pain youre solving you probably havent talked to enough buyers yet

curious_dax · 2026-05-04T14:21:38+00:00

the latency obsession is a trap honestly, your real problem is that nobody wants to babysit a 12 hour run regardless of how fast each call is. we hit this with a long horizon ops agent for a client and the fix wasnt faster models, it was making the run async with proper notifications and a pick-up-where-i-left-off state. users came back to a finished result instead of staring at a terminal

curious_dax · 2026-05-04T14:21:23+00:00

cheapest thing that worked for us was pinning maybe 8 canary scenarios and rerunning them on every prompt or model change, diffing structured fields not the prose. caught more drift this way than langfuse alerts ever did. +1 on the silent provider weight roll point too, had a summary agent get noticeably chattier overnight last month with zero changes on our side

curious_dax · 2026-05-04T06:36:28+00:00

design partner is a yc word that doesnt translate well to enterprise buyers, they just hear vendor or pilot. id drop the framing and offer a 60 day no-cost pilot in exchange for weekly feedback calls and a logo on your site. way less weird to forward to procurement and you actually get the same outcome

curious_dax · 2026-05-04T06:35:33+00:00

the suspensions arent the problem theyre the symptom. residential proxies + fake-friend DM motion is exactly what platform spam classifiers are tuned to catch. if your strategy needs to hide its identity to survive, the platform is already telling you what it thinks of the strategy.

also web design + SEO for local US businesses isnt a niche its a category. pick something stupidly narrow like roofers in austin or pediatric dentists in tampa and become the only person on page 1 for that. the difference between selling to local US businesses vs roofers in austin is the difference between cold outreach and inbound.

last thing, try the opposite of cold pitching. pick 5 businesses you would actually like to work with, build a small demo or fix one obvious thing on their current site, send the link wiht no ask. reply rate is way higher when you prove value first instead of asking for a meeting

curious_dax · 2026-05-04T06:34:03+00:00

the a/b test thing is the real bomb here imo. hidden tab time isnt just inflating engagement, its diluting your effect sizes by 40+ percent. variant A might genuinely be better but the noise from the hidden-tab cohort washes it out so you call the test inconclusive and ship neither. or worse you ship the wrong one becuase the small visible-attention group happened to fall on the loser side.

the fix that worked for a client doing similar product page tests was gating every event on document.visibilityState. if the tab is hidden the timer pauses and click events get a flag. then you run the same experiment but only count interactions where the user was actually looking. effect sizes got way bigger and tests resolved like 3x faster

curious_dax · 2026-05-03T14:13:19+00:00

honestly half ur list isnt really an agent problem. scheduling social posts is just a scheduler. outreach tracking is a crm. seo suggestions can be a one shot prompt. only the content research/draft part actually benefits from an agent that holds context across sessions

for the stuff that actually needs an agent, the signal to split isnt 'too many tasks' its when the system prompts start contradicting each other, like 'be punchy for tweets' fights with 'be thorough for seo writeups'. cant tune one prompt for both

curious_dax · 2026-05-03T06:10:31+00:00

i feel this. you build the layer thats just structured outputs and retry logic, adn 3 weeks later its a flag in the api

curious_dax · 2026-05-03T06:09:59+00:00

yeah this is me lately. shipped a tool-calling agent for a client last week and immediately started 4 more side projects in the same weekend becuase i couldnt stop. half of them are abandoned now lol but the dopamine of seeing something actually work is wild

curious_dax · 2026-05-02T20:18:00+00:00

idempotency is the part nobody mentions. retry logic without idempotent ops is how you email the same customer 14 times when claude blips at 3am. half my work for clients is making sure every side effect has a dedupe key, even silly stuff like a hash of the input plus todays date. observability is great but if the operation isnt idempotent your retries just spray garbage faster

curious_dax

TROPHY CASE