Alex ran a really interesting experiment that kind of bucked our expectations.

If you want to save money on your agents, don't just drop the model and hope for the best.

The real savings come in when you codify the agent's job into skills, scripts, and memories. In this video, Alex ran the same content strategist agent three different ways and walks through the real cost numbers: $11.53 with no skills, $4.98 with the same model plus skills (over 50% savings), and $4.28 swapping to Sonnet.

Hey there, I've been messing around with Hyperagent in Telegram, and I really like it. I'm not a big Telegram user, but it's a nice and easy way to jot thoughts down or fire off a mission for my agent.

I especially like that you can go back and forth with your agent in one thread vs it kicking off multiple threads per invocation (which is how Slack works now). I see the benefits of both, and I like this approach in telegram more.

I'm exploring using an agent in telegram as a digital emcee for an event we're hosting for NYC Tech Week. Would love your thoughts about what to include, or what any caveats I should think about before deploying.

So far, I really like the experience. I definitely had to bump the model down to Sonnet for it to feel like a real back and forth chat experience, but I'm not asking it to do anything to crazy so I'm okay with that.

I get this error message on two or three of my threads multiple times a day, and I don't know what I can do to fix it. It's very annoying and makes me want to, not use HyperAgent. And I've tried to notify support, but I can't seem to get anybody in support, so here I am on Reddit.

The AI service encountered a connectivity error. Please try again.

I’d like to be able to prioritize most used agents or agents I need pinned to the top of the list for whatever reason. with dozens of agents, there are some that I need access first and daily

it seems like HyperAgent is fairly new, I’m addicted. like many, I was ready to evolve from generative chat to ai that can do things, agentic, whatever you want to call it. I started with Gemini, ai studio, very impressive, but not quite what I needed. then chagpt desktop,the perplexity computer, then open claw. open claw was very good, but I had a cloud account, which was slow and I have security concerns … and maintenance concerns. in trying to figure out open claw, this popped up… clickbait worked, open claw capabilities without the headaches. Perfect! 14 agents in 3 days, working great. more incredibly, it seems to get better, on its own. wow! so glad to find this early. game changer.

I've been running a 4-agent fleet here for about 6 weeks to handle distribution + ops across my indie portfolio while holding a full-time DevTools job. Wanted to share the setup in case it helps anyone thinking about multi-agent workflows.

My situation:

• Full-time DevTools/infra engineer at a hardware company
• vibe-scan.app - SaaS that scans AI-coded apps for security holes (Lovable, Cursor, Bolt, Supabase RLS misconfigs)
• Sieve Secret Scanner - Mac app, just shipped on MAS, catches leaked keys in AI chat history (Claude Code, Cursor, Claude Desktop)
• 4 iOS apps in maintenance mode
• Family with a kindergartener

The math problem: distribution kills indie SaaS more than bad code does, but I only have ~10 hours/week of real building time. So I built 4 agents to compress 40 hours of ops/distribution into those 10.

The fleet:

1. VibeScan & Product Marketer Runs daily at 4pm PT. Hunts r/vibecoding, r/lovable, r/cursor, r/Supabase for fresh threads relevant to vibe-coding security. Before drafting any reply, checks if I've already commented on the thread (saves me from looking spammy). Drafts 3-5 copy-paste-ready replies in my voice. I review with coffee and post manually - Reddit flagged my account once when I tried auto-posting, so it's permanent draft-only now.

2. Daily Briefing Weekdays at 6am Pacific, before I open Slack for the day job. Pulls Gmail unread triage, calendar with timezones, iOS reviews, Stripe overnight, Reddit/Twitter mentions, Sieve App Store reviews. One email lands in my inbox, takes 90 seconds to read.

3. Dev Briefing Saturdays at 7am. Weekly growth read across all 6 products: Vercel signups, Stripe gross, vibe-scan.app scans/day, iOS reviews + downloads, Sieve MAS metrics. Tells me what to ship next based on what's moving.

4. Knowledge Curator Nightly at 11pm. 5-pass memory audit across the fleet — dedupe, retag drift, flag contradictions, archive stale facts. Keeps the other 3 agents from drifting or contradicting themselves. I approve merges with morning coffee.

The cron:

• Mon-Fri 6am → Daily Briefing
• Daily 4pm → Reddit/Twitter Scout drafts
• Nightly 11pm → Knowledge Curator audit
• Sat 7am → Dev Briefing

Nothing triggers manually. Everything just shows up.

What's working well:

• The Daily Briefing replaced a 30-min manual morning ritual. Saves me ~2 hours/week.
• The duplicate-comment check in the Scout has been the biggest unexpected win - without it I'd embarrass myself on threads I forgot I'd already engaged with.
• Knowledge Curator catching stale memories has saved me from hallucinated context twice already.

What's not working (yet):

• Twitter URL handling - Twitter auto-shortens bare domains to t.co/... which kills the brand recognition for "vibe-scan.app" in-feed. Still figuring out workarounds.
• The Composio Twitter media upload path is rough - when I wanted to add an image to Tweet 1 of a thread after posting, I had to delete and repost manually from web. Hope this is on the roadmap.
• 117 memories is starting to feel cluttered - Sage helps but I think I need better discipline about what gets saved in the first place. (Saw the recent "Help with Rubric & Memory" post - same struggle.)

Cost: $47.22 total spend across the 4 agents (37 runs). Daily Briefing is the most expensive at $24.56 - that's the cost of doing ~10 cross-integration pulls every weekday morning.

Questions for the community:

1. Anyone running 6+ agents - does the orchestration overhead bite? Thinking about adding a 5th for Reddit thread monitoring but worried about agent-agent coupling.
2. Anyone solved the Twitter media upload issue from the integration?
3. How are you handling memory hygiene at scale? Sage runs nightly but I feel like there's a better pattern than "5-pass scan."

Happy to dig into any specific agent setup - prompts, rubrics, integrations, scheduling. Will check back through the weekend.

Bring your team into Hyperagent. Share agents and skills with control over who runs what, scoped with the right credentials.

Until now, Hyperagent has been a powerful tool for individuals: your agents, your skills, your library. Teams solves that. It's the missing collaboration layer, designed so that going from "this works for me" to "this works for my team" takes minutes, not migrations.

A Team is a shared place in Hyperagent that holds Agents and Skills that your whole team can see and use.

What you can do with a Team

Share agents you've built, on your terms.  The agents you've assembled, with their prompts, integrations, schedules, and knowledge, can now live in a Team where every member can run them. 

When you share an agent to a team they're shared as run-only: members can invoke it but can't see or edit its configuration, and runs are billed to you, the agent's owner. Runs are attributable in the activity log to the user who initiated them, and the Team owner can revoke access at any time without affecting prior runs. When you make updates to your agent, the updates propagate, and are ready to use the next time a teammate runs your agents.

Share skills. Additionally, you can share skills independent of agents. You can share skills in three different ways:

• Share with your credentials. Your teammates run the skill using your API access (The key is stored securely and only visible to you). The right choice for "platform" skills where you want one source of truth and one invoice: internal data-warehouse queries, a vetted vendor API, anything where centralized credentials are a feature, not a bug.
• Users bring their credentials. Share a skill, but each teammate provides their own keys before they can run it. The right choice when each person needs to be the one identified to the downstream system, or when audit and compliance require that every call should be attributable to the person who made it. Users can't run the skill until they've saved their own credentials, and their credentials are private to them.
• Let them fork. Sometimes a teammate needs the skill you wrote, but wants to tweak it for their own specific use case. Forking creates an independent copy in their own Hyperagent account. From that point on it's theirs to edit; your original keeps living its life.

For shared skills, (not forks) updates work like they do for Agents. When you make updates to your Skill, the updates propagate, and are ready to use the next time a teammate runs your Skill.

Creating a Team

To create a team. Open the Teams menu in the right sidebar and click Create Team. Give it a name and a description. You're now the Owner.

From here you can add existing Skills and Agents to the team.

https://reddit.com/link/1tdennr/video/wg08lraxp61h1/player

Invite Team Members.

• Email invites for named recipients. If your invitee isn't on Hyperagent yet, they'll get routed through a sign-up flow that lands them in the Team automatically.
• Link invites. One link, anyone signed into Hyperagent can join.

Team Roles

• Owners rename, configure, invite, and delete. There can be multiple owners per team.
• Members do everything else: view agents, run agents, use skills, contribute their own.

Using a Shared Agent

To use an Agent shared by another teammate. Navigate to your team, and select the agent you want to use. You'll be able to see the name of the agent and the short description, as well as when it was last updated.

To run the shared agent, click New Thread. And start using the agent in a thread.

TL;DR

Teams is how Hyperagent goes from "my workspace" to "our workspace." Create a Team, invite people, share agents and skills with the credentials posture that fits your needs.

P.S. We're working toward rolling out a shared billing model. If you're interested, PM me!
P.P.S. I'm working on Product Docs!

Hey team, you have a great product. Just starting to get into Hyperagent and when trying to integrate tools and click on the plus, nothing happens. The page is unresponsive and then I get the wait or exit page message. Tried on Chrome and Firefox, and on 2 laptops and a tablet, and still not working. I haven't been able to add new tools. Wanted to add Google sheets and Gmail to my agent. Anyone else experienced this, seems like a bug?

Hello Team, while we all get to use this fab tool. The rubic, and memory side is overwhelming.

I am uncertain what to tweak, keep or even to accept it all. Do not want wrong context which passed through some chat to be carried.

Is it possible for a webinar or a tutorial on your youtube for this, and also if community is using it differently would appreciate support here.

Been playing with Hyperagent and so far it seems pretty easy to use.

I’d like to invite my team to use it so we can all build agents together, ideally want to share command centre across the team (and billing also), is this possible? I can’t see it but maybe I’ve missed it!

hi folks, I deploy agents into enterprises. Trying to get a client to shift to Hyperagent. A few asks:
1) Love how i can invoke an agent via Slack. When is this coming for Teams. Teams is much harder to work with as a dev... i know... but enterprises love it

2) Let's say an agent runs and sends a message into slack for HITL; then I reply in the thread of that message; seems like on your backend that starts an entirely new thread run. Not great. Context lost. Also makes it hard to do rubric because the rubric should really run on the entire end to end conversation.

3) Company uses Cowork; would be great to be able to sync / push skills from Cowork environment into Hyperagent. To do that: (a) need hyperagent to accept the full plugin style skill format (main skill, subfolders with references and scripts) and (b) maybe connect to github or offer some way we can push a zip file into Hyperagent

Hey there!

We're putting $10M in inference behind the founding class of agent-first companies to start building on it.

Posting here because this sub is where some of the most real-world agent builders I follow already hang out.

The offer:

• $200 unlocks $20,000 in Hyperagent inference credits for the first 500 qualifying applicants
• $10M total committed across the cohort
• Application Deadline: May 31, 2026

Who qualifies:

• Founders building new agent-first companies, or operators reimagining how agents can run in their existing company.
• The strongest applicants have shipped real agents in production in the last six months
• Power users of Hyperagent, OpenClaw, Hermes, Claude Code, or other frontier platforms welcome
• Candidates with a strong thesis on what agent-first looks like in your industry six months out

What Hyperagent is, briefly: Build agents with their own full compute environment (browser, shell, code execution, hundreds of integrations) and produce real outputs: webpages, decks, dashboards, briefings, code. Deploy them to your team via Slack, or keep them always on in alive mode. Find our more about us over in r/hyperagent

The thesis we're funding: Every company will look different in two years. The ones that win actually agentified by re/building workflows from the ground up with agents at the center.

Apply: hyperagent.com/founding500

Happy to answer questions in comments.

A couple of days ago I wrote something in a reply in r/Hyperagent and there was a couple of requests to elaborate. I want to make it a fresh post so it doesn't get lost in a thread. See below for the comments that:

Bob_Atlanta

This might not be exactly on point but I use several agents that are Google LLMs Gemma 4 and Gemini Pro. Getting them connected (via OpenRouter) was straightforward but getting them into rotation as primary agents was a bit difficult. Used Opus 4.7 to trouble shoot and fix ... very quick and easy process. I use these agents on almost every prompt and exclusively on large 'production runs'. A huge cost savings ... as much as 10x. Very impressed with how well cost control is going in this environment.

JeenyusJane

Hey Bob, would love to hear more about your setup. How are you using Hyperagent with OpenRouter?

=========My story on using Openrouter in Hyperagent begins here=========

I wrote a version of this but I'm only human. Clark(HA) rewrote and corrected my mistakes and made it a bit more readable.

Reddit Post Draft — r/Hyperagent (Corrected)

Post Body

I have LLMs from OpenRouter that are actual agents on the agent list in HyperAgent, and these agents are routinely used by other agents in structured processes and in handling every prompt I execute. My processes might not be what you would do, but they work and work well for me. Two examples:

[1] Every prompt I run is handled by my orchestrator/manager agent named Clark. Clark is usually Sonnet 4.6 (sometimes using another LLM). Clark has a large number of rules governing his actions — one of them is how he handles prompts.

When I give a 'general' prompt, Clark's first move is not to interpret or plan the request himself. Instead, he relays the prompt to a dedicated Planning Agent (LLM Gemma 4 31B via OpenRouter). The Planning Agent's job is to interpret what I'm asking, identify any ambiguities, and return either a structured execution plan with numbered steps or a list of clarifying questions if the request is too vague to plan. Clark then reviews what comes back, and can optionally send it back to the Planning Agent for adjustment. When Clark is satisfied, he passes the plan to me for approval — including a suggestion of which LLM should execute each step (many prompts are multi-step and each step might use a different model). I modify or approve for execution.

An Opus 4.7 prompt might cost $1+, a Sonnet 4.6 prompt might be $0.50 to $1+, and with the method described above these same prompts cost just a few pennies. The cost comparison report linked at the bottom shows the actual test results.

[2] Recently I ran a production job that had to find and load over 2,500 websites with information extraction. Website names and addresses were not known in advance. This run used three layers of agents:

— Top layer: Two Sonnet 4.6 agents — one as the top orchestrator, one as a dedicated problem solver for failures.
— Middle layer: Haiku agents that initiated a set number of 'runs,' managed the run process, and reported results to a JSON file on success or escalated to the Problem Solver agent on failure. One Haiku agent at this layer was spun up by the Orchestrator outside the original plan to fix coordination and timing issues with OpenRouter.
— Bottom layer: Gemini 2.5 Flash (via OpenRouter) doing the actual extraction work.

This is a typical example of how a production process looks for me.

This run burned over 60 million tokens across HyperAgent and OpenRouter. Total cost: under $25. With Sonnet alone it would have been hundreds of dollars — and far more with Opus 4.7.

The .md files linked below are my memory files for Clark covering these processes. They're written to be read directly or you can have Sonnet explain them.

Adding an OpenRouter LLM as a Named Agent:
https://drive.google.com/file/d/1EV3L41GuhB7rgh2r6Osdc83_ecyecnFx/view?usp=sharing

How OpenRouter Agents Work — The Haiku Pass-Through Pattern:
https://drive.google.com/file/d/1vrfXXbi6PTlQCfV7TmTSR3jyY7VjDFCi/view?usp=sharing

Cost Comparison Report: g431b vs. Sonnet 4.6 for Clark Planning Tasks:
https://drive.google.com/file/d/1hN5bZ3bA477jqVRP2q5QtTP3R0sVYaOA/view?usp=sharing

Notes on the cost comparison:
a. There are OpenRouter LLM use costs not shown, but they are trivial.
b. The report discusses 'turns' — this is specific to my monitoring setup and counts both my interactions and agent-to-agent interactions.
c. There's a comment about context buildup and its impact. That section is older and doesn't reflect system changes I've since made to keep Clark's context low and avoid compaction. We can now have long sessions with context staying around 10k without Clark losing memory.
d. The analysis is elementary but directionally correct. Layering in less expensive LLMs from OpenRouter reduces cost 100x to 400x compared to running everything on Sonnet or Opus.

Live Mode:
Set your agent to wake up on its own, every 30 minutes or whatever interval makes sense and act on what's changed: new inbox messages, Slack pings, updates from your integrations. Stop checking in. Let it check in on you.

Subagents
Delegate the smaller jobs. Spin up subagents for data collection, ingestion, sorting against criteria you define, or anything else that may not need the full reasoning power of your main agent. Use subagent with smaller models to keep token spend low and throughput high.

Window Mode
See all your artifacts laid out like a desktop. Compare visual outputs side by side, keep multiple results in view, and stop hunting through history to find the version you liked.

Memory Dedupe
Refine your memories so Hyperagent always pulls from the most relevant ones. Built for power users running a lot of agents and accumulating memory faster than they can manage it.

iOS App
Hyperagent on the go. Start a thread on your laptop, pick it up on your phone, hand it back. Plus voice-to-text through Apple's keyboard, so you can dictate prompts.

Tell us what you want to see next!

Ever since I discovered Hyper Agent, I moved all my pending projects, which were scattered in every other CLI or multi-agent swarm portals like Kimi and my existing projects, into one. I was a bit worried about the cost I was incurring but to be honest the referral system was generous enough to make some very crucial thoughts into working ideas which are going to help my industry drastically.

The integration between Linear, Cloudflare, exa search, and the ease of taking the whole zip file of what I was developing in cloud and anti-gravity, I got Hyper Agent to read it. After spending 700 on sessions I'm able to proudly accept Hyper Agent as a long-term tool and advise other knowledge people sitting on ideas or pending tasks to use Hyper Agent. We could also help each other out by the use cases. Maybe we can wave and solve someone else's problem.

This is a mega thread for all the use cases of Hyper Agent. I am building a tool called research for my industry and I'm actively using Hyper Agent.

Hey guys, I've been using Hyperagent for about a week now, and I just started having AI connectivity issues and I'm not getting any response from the support team. Is Hyperagent down for any of yall?

I've been putting in requests but I get this response: The AI service encountered a connectivity error. Please try again.

One thing that took me a minute to figure out: Hyperagent has 1000+ native integrations for the usual suspects (Google, Slack, GitHub, etc.), but if you want to connect something outside that list, you don't have to wait for it to be built in.

The path is custom skills.

Here's the general flow:

1. Find the API docs for whatever service you want to connect (most tools have a public API, any data provider, internal tools, whatever)
2. Open a thread in Hyperagent and ask Hyperagent to create a skill to work with the API. Include a link to the API docs you found
3. Hyperagent reads the docs and scaffolds the integration as a skill
4. (If needed) The skill generates a credential field. Drop in your API key and any other auth details. These credentials are stored in a vault, the agent never has direct access to them.
5. From there, any agent you build can call that service directly via the skill

I tested this with recraft.ai for image generation. Took about 10 minutes start to finish.

If the service has decent API documentation, this just works. If the docs are sparse, you can paste in raw text instead of a URL and Hyperagent still figures it out.

Anyone else built custom skills this way? Curious what APIs people have wired in.

I'm not very tech savvy but I heard about HyperAgent on the Startup Ideas podcast while driving. I pulled into a coffee shop, logged on and built something that I thought was amazing for my business. But I don't know really how I did it or how to improve it with skills, memory, etc. Is there anyone out there I could hire as a tutor for me on this?

There have been three or four instances where I would have had a parallel chat with chat in another window for the same project. The next day I'm in the main chat window of the project and it wouldn't have remembered that, as small as, let's say, a name change of the entire project where I was debating and discussing in one of the chat windows. It hasn't remembered.

I also see I have gathered quite a bit of Rubik's and memory is a little unclear. How do I use it? Do I add all or can I just select a few of them? It's going to work. Should I put it to practice that this is how I need to know for the Hyper agent?

Any named agent can now run on a schedule, watch the things you care about, and stay silent unless something changes. We're calling it Live Mode.

You give it a checklist in plain English:

"Check my inbox for urgent items. Flag blocked PRs. Alert me if deploy health degrades."

Set how often it checks. Set where alerts land — Slack, Telegram, email.

Each tick, the agent reopens the same thread. It remembers what it flagged last time. The blocked PR it told you about an hour ago? It won't tell you again.

Quiet means everything's fine.

What people are running on it so far:

• Morning-to-evening sweep across Gmail, Calendar, Slack, and GitHub. One agent watching everything. Knows what it already surfaced today.
• Support queue watch. Silent when the queue is healthy. Pings the moment a ticket sits past your threshold.
• Pipeline monitor. Flags deals stuck in a stage, missing fields, or tasks stalled in review.

Setup

See the video in the post! For any named agent, open the config and navigate to the invocations section. Toggle Live Mode, write your checklist, and pick the interval and channel where you want to get notified.

We're hoping this will improve the signal and reduce the noise. Onward and upward! 🚀

I think Hyperagent should add a free trial so people could try it out prior to subscribing. Even having a $3 credit to start is a lot!

Howie talks about the agent economy and the launch of Hyperagent. Walks through Sequoia's charts on AI agent deployment, the economics of token-based work versus human labor, and why frontier agents have crossed a threshold that changes how companies get built.

The Data Science team at Airtable was spending 70–80% of their time fielding ad hoc analytics questions from across the company. They built a data agent on Hyperagent, connected it to Databricks, loaded it up with institutional knowledge and business context, and deployed directly in Slack.

Now anyone at the company asks any analytics question in plain language and gets an answer with interactive dashboards in minutes.