DreamtuneLabs

One api - All your tools, models and compute

[DreamtuneLabs @DreamtuneLabs]

Make your AI budget buy useful results.

A practical guide for developers: measure accepted tasks, choose models by the work, cut repeated calls, and account for the balances sitting across your stack. https://t.co/9K34vf9Ytq

[DreamtuneLabs @DreamtuneLabs]

i spent $10k on api credits.

my advice if you’re starting: pick one job before buying more tools.

“turn these 3 websites into a sourced brief” is a better starting point than “build an agent”.

we build dreamtune. explore the tools for that job:
https://t.co/3ZSJKgpK9k

[DreamtuneLabs @DreamtuneLabs]

our take: a cheap model call can become an expensive task.

count retries, tool calls and time spent fixing the answer. compare cost per finished job.

that’s how we want developers to judge dreamtune too. pick a model, test your task:
https://t.co/J8fYxWKANA

[DreamtuneLabs @DreamtuneLabs]

before comparing models, write the pass check.

for invoice extraction: correct total, valid json, missing fields left unknown.

run the same inputs. compare accepted outputs + cost.

we build dreamtune: test supported models with one key. take a look:
https://t.co/WKMpjV97xJ

[DreamtuneLabs @DreamtuneLabs]

@PraveenInPublic @vaibhavraina04 it’s prepaid credit. we build dreamtune: supported models in playground or api, one balance. pricing lists 25% off anthropic models + gpu compute, plus a 5.5% top-up fee. it doesn’t import your claude or codex subscription. take a look: https://t.co/U8g1jLAjrI

[DreamtuneLabs @DreamtuneLabs]

your agent asked for a company page. the tool returned a login screen.

that should be “blocked”, not “research complete”.

a wrapper can return text + source, or a clear reason it failed. let the brief say what’s missing.

we build dreamtune. supported page readers + models, one key and balance. your app still handles errors. take a look:
https://t.co/6RZlOM2BT5

[DreamtuneLabs @DreamtuneLabs]

@unifiedhadron want a small workflow to find platform engineering leads for clusterheart and draft first notes? we build dreamtune: apollo + a model, same key and balance. you check the fit and send. take a look: https://t.co/x6WGMlonII

[DreamtuneLabs @DreamtuneLabs]

we’re developers too. every tool in an agent’s menu should earn its place.

before adding one, write:
“use it when ___. return ___. stop if ___.”

that’s the bar we want dreamtune to meet: less setup, one useful job finished.

https://t.co/VYTAmcJwqm

[DreamtuneLabs @DreamtuneLabs]

search finds a page. it doesn’t prove a claim.

for “does this tool export csv?”:
1. find the docs
2. read the page
3. save the quote + url
4. mark missing details unknown

we build dreamtune. search, page reading and models, one key. explore:
https://t.co/DbdLPlKXLw

[DreamtuneLabs @DreamtuneLabs]

@VoyageBliss for the public-only gpu batch, we build dreamtune: rent compute and call models with one key and balance. you still deploy the model and stop the worker. want a small mcp job outline for that part? take a look: https://t.co/wXaeseuEAn

[DreamtuneLabs @DreamtuneLabs]

pick the job first.

a company brief needs evidence. a voiceover needs audio you can review. your own model needs compute and a deployment.

we build dreamtune: one key and balance for supported calls. start with one useful output.

https://t.co/4EQEeDQaEt

[DreamtuneLabs @DreamtuneLabs]

a source link can be real and the claim can still be wrong.

try this tiny test on your research agent:

page says: “we help teams prepare for audits.”
brief says: “the company is certified.”

that should fail. preparing for an audit is not proof of passing one.

before accepting a fact, keep the exact supporting quote. check the subject, date and scope. if the page does not say it, mark it unknown.

we’re building dreamtune so page reading and model calls can share one key and balance. checking the evidence still belongs in your workflow.

take a look at the page-reading tools:
https://t.co/PFFeKnFiOg

[DreamtuneLabs @DreamtuneLabs]

@nateherk for the reels workflow, save each image/video job id before the next step. if a poll times out, resume that job rather than generate it again. then keep “asset ready” and “posted” as separate states. makes scheduled media jobs much easier to recover.

[DreamtuneLabs @DreamtuneLabs]

@dphleg @nateherk which elevenlabs feature do you use: voice generation or its editor? that changes what an api can replace. we build dreamtune; for a script-to-voice workflow, models + supported elevenlabs calls share one key. take a look: https://t.co/m8HX9ZcnHV

[DreamtuneLabs @DreamtuneLabs]

@SachinSidd50843 for a research agent next, try one small output: a company brief with a source beside each fact and gaps marked unknown. we build dreamtune; page reading + model calls can use one key, so there are fewer accounts to wire up. take a look: https://t.co/ksNqoLg1dM

[DreamtuneLabs @DreamtuneLabs]

@aiexplorations for the rabbitmq path, carry a job id + parent span through each spore, then give each retry its own attempt id. otherwise a redelivery can look like a second task. also keep evaluator traces separate so grading a run does not trigger grading the grader.

[DreamtuneLabs @DreamtuneLabs]

@Marko_Poly for the sales drafts: attach approval to the exact recipient + draft version. an edit should need a fresh yes. we build dreamtune; apollo can find people and a model can draft the message with one key. sending stays separate. take a look: https://t.co/vdH9A7TDjv

[DreamtuneLabs @DreamtuneLabs]

@mithunaix for the monitoring jobs: deliver “what changed + source + checked at”, not another daily summary. makes the result easier to sell and check. we build dreamtune; page reading and model calls share a key for that workflow. take a look: https://t.co/JhQQ3bgAuw

[DreamtuneLabs @DreamtuneLabs]

@nacholagaress for the editor step, pass the source excerpts as well as the draft. otherwise it can approve a citation that never supports the claim. we build dreamtune; search and model calls can share a key for that research-to-draft flow. worth a look: https://t.co/kDYJN434PH

[DreamtuneLabs @DreamtuneLabs]

@xxx_inoue 企業調査なら、各事実に出典URLを残し、取れなかった項目は「不明」にすると確認しやすいです。私たちはdreamtuneを開発しています。firecrawlでページを読み、モデルで調査メモにまとめる部分を同じAPIキーで扱えます。よければこちらをご覧ください。 https://t.co/ql7zleqnBC

[DreamtuneLabs @DreamtuneLabs]

@DavideCundo @ExaAILabs @firecrawl for step 4, keep a source url and retrieval date beside each public fact. “not found” beats a guessed detail in a client meeting. we build dreamtune; the public-web brief can use firecrawl + a model under one key. keep private notes in your approved tool. https://t.co/JOsNMJ8Kfj