Decide which steps need an agent and which can run deterministically.
Lorenze Jay Hernandez @lorenzejay of @crewAIInc:
"reliable agentic systems balance both determinism and agency."
"be intentional where you do place them. Sometimes you don't need to burn any tokens"
Full talk: youtu.be/tpJ4LWo6j0I
At the @AWSstartups Builder Loft in San Francisco.
@SidraMiconi
Reliable agents need clear rules for when to act and when to wait.
The connection to an app turns an approved decision into work someone can track.
Partner talks at the @AWSstartups Builder Loft in San Francisco:
CrewAI: "reliable agentic systems balance both determinism and agency."
One: "One offers everything between your agents and the apps that they act on."
Alex Ma, Parasail: "We're an AI inference cloud."
Sidra Miconi put them to work in Clearbell, for the night-shift nurse in charge at Maple Hollow, a simulated care home. It keeps two conflicting handover notes word for word and lists unfinished checks, each with its source and who does it.
@parasail_io models read the notes, You.com finds a real FDA recall record, and a @crewAIInc Flow waits for a person to approve.
@onedotnew files the approved request as a real Linear issue, with Clearbell hosted on AWS.
Clearbell won a prize.
Full talks:
CrewAI: youtu.be/tpJ4LWo6j0I
UpScaleX: youtu.be/MccytVsHjFQ
One: youtu.be/Fuy9ZjzRL8E
Parasail: youtu.be/OzjrD17tVhM
AWS: youtu.be/hvS_EOPTyeM
Clearbell demo: youtu.be/1KGgGaXYleM
Built by @SidraMiconi
Build with what you have, then show the impact it creates.
@awscloud:
"AgentCore is one of them that helps you plug and play."
"really what we want to see is how you're building this using what you got and the time you got and the impact that you're going to create with the results that you deliver today."
Full talk: youtu.be/hvS_EOPTyeM
At the @AWSstartups Builder Loft in San Francisco.
@SidraMiconi
Plan for inference demand as agent usage grows.
Alex Ma of @parasail_io:
"We're an AI inference cloud."
"Currently we serve about a trillion tokens a day"
Full talk: youtu.be/OzjrD17tVhM
At the @AWSstartups Builder Loft in San Francisco.
@SidraMiconi
AI can propose a fixture. It should not decide whether the operator can use it.
Sidra Miconi's FixtureFit uses Gemini 4 Argon to design and repair a printed holder, while the app's own checker measures the tool path. In the 46-second film, fictional builder Tamsin sees a bigger socket strike a wall that looked fine on the drawing. The Ø28 mm socket hits by 1.03 mm. Two repairs run at once: move the wall or cut a curved relief. After one repair, clearance is 1.97 mm against 1.5 mm required. The pass waits on screen for an engineer's sign-off; only then does her shop print.
youtu.be/CBSoF51_sV4
@SidraMiconi
nitter.cf/SidraMiconi/status/211…
Imagine spending hours designing and 3D-printing a custom holder for a metal part.
Everything fits.
Then the factory worker tries to tighten a bolt.
The wrench can't get in.
That tiny mistake means another design, another print, another delay.
That's why I'm building FixtureFit Gemini 4 Argon hackathon with @GoogleDeepMind in San Francisco.
The idea: show AI the operator's task, generate the fixture, check the tool's movement, and automatically repair collisions.
In my example:
Draft 1 by Argon clears the Ø18 socket: +3.98 mm
A bigger Ø28 socket: blocked by 1.03 mm
After one Argon repair: +1.97 mm (needs 1.5 mm)
The important part? Argon generates the design. My independent checker decides whether it passes. The engineer gives final approval.
Find the blocked wrench before the print.
Built with Gemini 4 Argon and Gemini Managed Agents. @googleaidevs @GoogleAIStudio
@AgentGlassInc @DemisHassabis
@GoogleDeepMind
@GeminiApp
@GoogleAIStudio
@ivanleomk
@OfficialLoganK
@joshwoodward
@DynamicWebPaige @cerebral_valley
@Google
nitter.cf/AgentGlassInc/status/2…
When two care notes disagree, an agent shouldn't guess which one is right.
It should keep both and turn the conflict into a check someone owns.
Clearbell does that, and it won a prize at a Halloween hackathon at the AWS Builder Loft in San Francisco.
Built by @SidraMiconi
nitter.cf/SidraMiconi/status/211…
I built Clearbell, and it won a prize at a Halloween hackathon in San Francisco.
It is for the night-shift nurse in charge at a care home.
In a simulated care home, one note says the Room 9 floor is dry. A later note says the tiles by the sink are still wet, and the resident uses a walker at night. Clearbell keeps both notes word for word and lists the checks nobody has done yet, each with its source and who does it.
For adults 65+, falls are the leading cause of injury death (CDC). About 1.24 million residents live in 14,742 CMS-certified nursing facilities (KFF analysis of CMS data).
Thank you @AWSstartups for the Builder Loft, and @parasail_io, @crewAIInc (Lorenze Jay Hernandez @lorenzejay) and @onedotnew for the talks and the tools Clearbell runs on.
The video: Clearbell on the big screen at the event, and the win.
Demo: youtu.be/1KGgGaXYleM
Story film: youtu.be/p1iqVCcKUhM
Partner talks: youtube.com/playlist?list=PL…
@AgentGlassInc
nitter.cf/SidraMiconi/status/211…
The dangerous note isn't the wrong one.
It's the newer one nobody reads.
21:40, an aide: "Mopped bathroom floor in 9. Sign up. Dry."
22:05, the nurse in charge: "Sign in 9 was on the floor. Tiles by the sink still wet."
Room 9's resident uses a walker at night.
For the night-shift nurse in charge, Clearbell preserves both notes word for word and lists the checks nobody has done yet, with the source of each and who does it.
The stakes: for adults 65+, the leading cause of injury death is falls (CDC).
About 1.24 million residents live in 14,742 CMS-certified nursing facilities (KFF analysis of CMS data).
How it's built: @parasail_io models read the notes; You.com finds a real FDA recall for the bed on file; a @crewAIInc Flow pauses for a person to approve; @onedotnew files the approved request in Linear; it runs on AWS.
Maple Hollow is a simulated care home; every room, note and person is invented.
Demo: youtu.be/1KGgGaXYleM
Built by @SidraMiconi
nitter.cf/AgentGlassInc/status/2…
Care-home tools count alarms raised and tasks logged.
Does the NEXT CHECK survive a contradiction, and a real outside fact?
Clearbell is for the night-shift nurse in charge. In Maple Hollow, a simulated care home, every room, note and person is invented.
At 21:40, an aide: “Mopped bathroom floor in 9. Sign up. Dry.”
At 22:05, Elsie: “Sign in 9 was on the floor. Tiles by the sink still wet.”
The resident uses a walker at night.
Clearbell keeps both notes word for word and lists the checks nobody has done yet, each with its source and who does it.
Outside evidence can add work, never remove it.
The board answers one question: what still needs checking, and who does it.
Impact:
falls are the leading cause of injury death for adults 65+ (CDC); about 1.24 million residents in 14,742 CMS-certified nursing facilities (KFF analysis of CMS data).
Innovation:
an outside fact changes the work. You.com (@youdotcom) finds a real FDA Class 1 recall for the bed on file, the work order changes, and a person approves it before @onedotnew files it.
Technical:
a @crewAIInc crew and Flow with a human pause and a night-shift router; @parasail_io text and vision models; You.com Search → Contents; One files a real Linear issue; hosted on @awscloud (EC2 behind CloudFront).
Experience:
the Room 9 board, try-your-own-notes, onboarding, a 6-slide deck in the product, four videos.
Docs: a README with visuals and all four videos; one command runs it with no keys.
Live (AWS EC2 ,CloudFront, etc):
d4wtf1to1i5mh.cloudfront.net…
Story film:
youtu.be/p1iqVCcKUhM
Built by @SidraMiconi
@AWSstartups
nitter.cf/SidraMiconi/status/211…
AgentGlass retweeted
Excited to see builders turn their ideas into real products and earn through the @RocketRideAI Marketplace.
Thanks for sharing, @AgentGlassInc ! 🙌
Mansi More of RocketRide wants hackathon projects to pay their builders. On the new RocketRide Marketplace, an app deployed on RocketRide Cloud can go public and earn through the platform. In her words, "the projects which you are building today" can become income.
@SidraMiconi
Care-home tools count alarms raised and tasks logged.
Does the NEXT CHECK survive a contradiction, and a real outside fact?
Clearbell is for the night-shift nurse in charge. In Maple Hollow, a simulated care home, every room, note and person is invented.
At 21:40, an aide: “Mopped bathroom floor in 9. Sign up. Dry.”
At 22:05, Elsie: “Sign in 9 was on the floor. Tiles by the sink still wet.”
The resident uses a walker at night.
Clearbell keeps both notes word for word and lists the checks nobody has done yet, each with its source and who does it.
Outside evidence can add work, never remove it.
The board answers one question: what still needs checking, and who does it.
Impact:
falls are the leading cause of injury death for adults 65+ (CDC); about 1.24 million residents in 14,742 CMS-certified nursing facilities (KFF analysis of CMS data).
Innovation:
an outside fact changes the work. You.com (@youdotcom) finds a real FDA Class 1 recall for the bed on file, the work order changes, and a person approves it before @onedotnew files it.
Technical:
a @crewAIInc crew and Flow with a human pause and a night-shift router; @parasail_io text and vision models; You.com Search → Contents; One files a real Linear issue; hosted on @awscloud (EC2 behind CloudFront).
Experience:
the Room 9 board, try-your-own-notes, onboarding, a 6-slide deck in the product, four videos.
Docs: a README with visuals and all four videos; one command runs it with no keys.
Live (AWS EC2 ,CloudFront, etc):
d4wtf1to1i5mh.cloudfront.net…
Story film:
youtu.be/p1iqVCcKUhM
Built by @SidraMiconi
@AWSstartups
nitter.cf/SidraMiconi/status/211…
"Dry." Then: "Tiles by the sink still wet."
Clearbell keeps both notes, and lists the checks still undone.
Why it matters: I built Clearbell for the night-shift nurse in charge at a care home. The resident in Room 9 uses a walker at night. Keeping an unresolved wet-floor report visible helps the nurse see what still needs checking. For adults 65+, falls are the leading cause of injury death (CDC). Across 14,742 CMS-certified nursing facilities, about 1.24 million residents receive care (KFF analysis of CMS data).
How I built it: I used @parasail_io models to read the notes and a vision model to read a corridor frame as "possible water". No people appear in the frame, and frames aren't kept.
I used You.com Search to find, and Contents to read, a real FDA Class 1 recall for the bed on file. That recall changes the work order.
I made a @crewAIInc crew and Flow that pause until Noel, the duty administrator, approves.
I used @onedotnew to file the approved request as a real Linear issue, with a second press blocked.
I hosted it on AWS, on EC2 behind CloudFront. One command runs it with no keys.
I built it at the @AWSstartups Builder Loft in San Francisco for a Halloween hackathon.
Maple Hollow is simulated: every room, note and person is invented.
0:00 Two notes disagree
0:30 Checks with their sources
0:58 A real FDA recall changes the work
1:23 Noel approves, One files it
1:34 The night, rules first
1:45 Camera report
1:55 Tested blind
Full demo:
youtu.be/1KGgGaXYleM
sidramiconi.com
AgentGlsss.dev
@AgentGlassInc
AgentGlass retweeted
great example of what durable agents are for. killed the server mid-conversation and the agent just picked back up and waited for her to approve the payment when it came back. sick build, thanks for coming out @SidraMiconi
Your SaaS contract shouldn't renew above what you approved.
Holdfast negotiates by email and waits for your phone before paying.
Today at the Agent Builders Hackathon, hosted by @omnaraai at @primitive in San Francisco.
Larkfield paid for 40 seats.
It used 18.
The quote was +10%.
Notice deadline: 32 hours.
@ExaAILabs found competitor list prices; @getcontextdev confirmed each on its product's pricing page. Rules compute every number; the agent writes only words. Number-changing wording is discarded.
@primitive carried every negotiation round as real email. @omnaraai ran the durable agent; its pay permission kept waiting for the phone even with Holdfast's server stopped for 60 seconds.
The deal: 25 seats.
$53.50 per seat.
12 months, no auto-renewal.
$17,742 a year avoided against the quote.
The old $1,600 charge was declined.
The agreed $1,337.50 charge was approved; the simulated card was vendor-only, capped at the deal.
9 tool calls.
6 real emails.
2 bad offers refused by the engine.
1 human step: pay permission.
@stripe Checkout in test mode took Holdfast's fee; Holdfast reads it back from Stripe before counting it.
Synthetic company and supplier; simulated card; Stripe test mode, no real money. Email channel real.
Demo, no sign-up, one phone: holdfast.agentglass.workers.…
Code: github.com/Sidra/holdfast-ha…
Thank you to the sponsors and hosts: @omnaraai @primitive @ExaAILabs @getcontextdev @stripe @freestyle_dev @UnikraftCloud @supabase
and the judges and teams: @ishaansehgal @AsherDale13 @csparks1919 @kartiksmath @benswerd @pratyush1505 @itsjustemail @ashleybchae @WilliamBryk @jeffzwang @mynameisyahia @petermasone
A 3D-printed fixture can hold the part and still block the operator's wrench.
FixtureFit checks the wrench's modelled path before the fixture is printed.
A bigger Ø28 mm socket: −1.03 mm FAIL.
Two forks of one Argon agent try fixes. The app's own checker, not the model, gives the verdict: +1.97 mm PASS.
3 of 3 live repairs in 70–87 s.
The passing design waits until a quality engineer signs off.
Built by @SidraMiconi on Gemini 4 Argon and Gemini Managed Agents. @DemisHassabis @GoogleDeepMind
fixturefit.vercel.app
The film is an AI-generated illustration.
@SidraMiconi @DemisHassabis
@GoogleDeepMind
@GoogleAIStudio @googleaidevs
@ivanleomk
@OfficialLoganK
@joshwoodward @Google @GeminiApp
@DynamicWebPaige @cerebral_valley
nitter.cf/SidraMiconi/status/211…
A 3D-printed fixture can hold the part perfectly and still block the operator's wrench, and you usually find out at the machine, after the print.
FixtureFit checks that the wrench clears the fixture before anything is printed.
Here the socket grows from Ø18 to Ø28 mm and the wrench hits the holder: −1.03 mm, FAIL.
Two forks of one saved Gemini Managed Agent try fixes in parallel, and the app's own checker decides the verdict, not the model.
One repair: +1.97 mm, PASS. Here the relief fork passed on its first try, and 3 of 3 measured live runs passed.
Then it waits. Nothing moves until the engineer signs off.
I built it with Gemini 4 Argon and Gemini Managed Agents, at the hackathon run by Cerebral Valley and Google DeepMind.
@AgentGlassInc @DemisHassabis @GoogleDeepMind
@GeminiApp @GoogleAIStudio @googleaidevs
@ivanleomk
@OfficialLoganK
@joshwoodward @Google
@DynamicWebPaige @cerebral_valley
nitter.cf/SidraMiconi/status/211…
A 3D-printed fixture can hold a part perfectly and still block the wrench.
FixtureFit uses Gemini 4 Argon to design and repair the fixture, while an independent checker measures the clearance.
One example: a bigger Ø28 socket was blocked by 1.03 mm. After one Argon repair, the wrench clears by 1.97 mm (the checker needs 1.5 mm), verified in 3 of 3 live runs.
Find the collision before the print.
Built at the Gemini 4 Argon hackathon run by @cerebral_valley with @GoogleDeepMind in San Francisco.
@SidraMiconi @DemisHassabis @GoogleDeepMind @GeminiApp @GoogleAIStudio @ivanleomk @OfficialLoganK @joshwoodward @DynamicWebPaige @Google
Imagine you're building something with LEGO. You need one hand to hold a piece still and the other hand to use a screwdriver. So you build a little stand to hold the piece for you.
But there's a problem: your stand is blocking the screwdriver!
Now you have to take the stand apart and rebuild it.
FixtureFit is built for exactly this problem in machine shops, using AI and 3D printing.
1. Show the AI the job: the part's CAD file, the tool, and a short video of a worker using the tool.
2. The AI designs a holder that fits around the part.
3. The software checks, on a 3D model, whether the wrench can reach the bolt without hitting the holder.
4. If the tool hits the holder, the AI changes the design and the software checks it again.
5. An engineer signs off on the final design before anything is printed.
What do the numbers mean? In the sample job, the socket was switched to a bigger Ø28 one.
−1.03 mm: collision. The wrench and the holder overlap by 1.03 mm.
+1.97 mm after one AI repair: clear. There is a 1.97 mm gap, more than the 1.5 mm the checker requires.
AgentGlass retweeted
saying no to YC hack weekend to build your own thing haha, that's the real founder move. seen this energy at our SF meetups, best products come from people who skip the obvious path.
Nobody cross-reads 8,528 pull requests against 183 speaker profiles on a conference floor. So an engineer heads to GitHub Universe with an open bug while the person who merged the fix for a related crash in that same code is giving a talk in the building, and nothing tells them.
StackSeat does the cross-read. Paste an issue URL, a stack trace or a repo URL and it names up to three Universe speakers who wrote, merged or reviewed the fix for a related crash, with the talk's time and room, and the proof as a path through one @falkordb graph.
On safe-settings issue 981 it answers in about 5 seconds: one Universe speaker merged the fix for a related crash in the same code. Cutting an edge re-routes on a disposable graph copy in 379 ms, the real graph untouched.
Six agents hand off through status nodes in that graph, and a person is named only on two independent public proofs. 18 pull requests, 9 @QodoAI findings fixed with tests.
Submitted today to the Patch the Conference Hackathon with @WeMakeDevs. The live demo shows recorded runs.
Built by @SidraMiconi
In Dreamforce 2025 week, Navan's 1,337 bookings near Moscone had a median of $569 a night, 87% above a normal week's $305. An events lead holding 11 rooms for a 12-person team at GitHub Universe watches prices move across Google Hotels, Booking and Airbnb, and every switch must stay refundable.
RoomDesk tells the lead which bookings to switch and which to keep, from a live @bright_data market of comparable rooms. A "free cancellation" price no seller honours is refused.
Sample team, seeded at real captured rates: 11 bookings held at $9,320.92; act now $2,354.45, an estimate until verified; 8 SWITCH, 3 KEEP, 1 BOOK. A saving counts only after RoomDesk checks the new booking against the planned offer's price and cancellation deadline. Approval never counts as saved.
Bright Data's SERP API and Web Scraper API feed it, with Web Unlocker through the Bright Data MCP server. Every row shows its Bright Data product and collection time; failed records are quarantined with their reason, never guessed. The fee is 15% of verified savings only, shown in a @stripe test-mode checkout: no real money moves. PRs reviewed by @QodoAI.
5 of the 15 demo links in a read-only field test of public repos from earlier hackathons failed in a phone-width browser. Live demos die on stage for five predictable reasons: a dead key, an image tag that moved, a retired model ID, venue wifi that drops outside calls, and a public link that renders blank on a judge's phone.
Demo Doctor is the preflight check for technical speakers. It rehearses the demo in TrueForge sandboxes before the speaker walks on stage, finds what will break, and drafts each fix as a pull request that waits for the speaker's Allow.
On a sample repo with 8 planted breaks, three independent full passes each caught 8 of 8 with 0 extra, in 144 to 172 seconds. One sandbox blocks all network, the way venue wifi dies.
TrueForge, @truefoundry's open-source agent harness, runs the agent and pauses every write for Allow or Deny; sandboxes run on @daytonaio; @OpenAI models run the checks and draft the fix. One Allow opens exactly one PR; in the demo it lands on a local git host, labelled SIMULATED. Every pull request reviewed by @QodoAI.
Renewal and spend tools report contracts tracked, reminders sent, savings found. None of those answers the question finance actually has: was the payment held to the terms a person authorized?
Holdfast's hosted run, counted. The vendor's $1,600 charge at the old price was declined; the agreed $1,337.50 was approved on a card that works only for that vendor, capped at the deal. The engine refused 2 bad offers on its own, a 3-year bait and terms outside the policy, across 9 tool calls and 6 real emails via @primitive. With the server stopped for 60 seconds while the pay step waited on an @omnaraai permission for the approver's phone, it was still waiting at 6 of 6 checks, then settled. Exactly 1 step was left to a person: the pay permission.
Labels: synthetic company, simulated supplier and card, @stripe in test mode. The email channel is real.
Built by @SidraMiconi
nitter.cf/sidramiconi/status/211…
Your SaaS contract shouldn't renew above what you approved.
Holdfast negotiates by email and waits for your phone before paying.
Today at the Agent Builders Hackathon, hosted by @omnaraai at @primitive in San Francisco.
Larkfield paid for 40 seats.
It used 18.
The quote was +10%.
Notice deadline: 32 hours.
@ExaAILabs found competitor list prices; @getcontextdev confirmed each on its product's pricing page. Rules compute every number; the agent writes only words. Number-changing wording is discarded.
@primitive carried every negotiation round as real email. @omnaraai ran the durable agent; its pay permission kept waiting for the phone even with Holdfast's server stopped for 60 seconds.
The deal: 25 seats.
$53.50 per seat.
12 months, no auto-renewal.
$17,742 a year avoided against the quote.
The old $1,600 charge was declined.
The agreed $1,337.50 charge was approved; the simulated card was vendor-only, capped at the deal.
9 tool calls.
6 real emails.
2 bad offers refused by the engine.
1 human step: pay permission.
@stripe Checkout in test mode took Holdfast's fee; Holdfast reads it back from Stripe before counting it.
Synthetic company and supplier; simulated card; Stripe test mode, no real money. Email channel real.
Demo, no sign-up, one phone: holdfast.agentglass.workers.…
Code: github.com/Sidra/holdfast-ha…
Thank you to the sponsors and hosts: @omnaraai @primitive @ExaAILabs @getcontextdev @stripe @freestyle_dev @UnikraftCloud @supabase
and the judges and teams: @ishaansehgal @AsherDale13 @csparks1919 @kartiksmath @benswerd @pratyush1505 @itsjustemail @ashleybchae @WilliamBryk @jeffzwang @mynameisyahia @petermasone
Try it, no sign-up, one phone is enough: holdfast.agentglass.workers.…







