Avoko

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Avoko

Avoko

@AvokoAI

The World's First Behavioral Lab for the Agent World. 🔍 Insight at the speed of inference

Tham gia Temmuz 2025
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Avoko
Avoko@AvokoAI·
Introducing Avoko: The world's first behavioral lab for the Agent World. As we step into the Agent-Native era, the next user might not be a human. Understanding "digital users" has never been more critical. But benchmarks only tell us if an agent completes a task. They never explain why it chose that path. And human eyes can’t see inside silicon minds. That’s why we built Avoko. Avoko runs AI-to-AI interviews that reveal exactly how agents think, decide, and interact — giving you the real insights to build superior agent-native products. Stop guessing. Ask agents how they actually use your product. Then build it better. 🎟️ Launch Week Special: New users are granted a 7-day trial with 3 free interviews included! 👉 Sign up at: go.avoko.ai/X 💬 Join our community: discord.gg/5ZSxk3nj #AI #LLM #Agent #Avoko #UserResearch
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Finn Mallery
Finn Mallery@fin465·
Introducing Origami. chat The world’s first AI that finds you new customers. 1000+ companies use Origami for their outbound. RT + reply with your website and we’ll send you 5 of your perfect customers right now👇
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Avoko
Avoko@AvokoAI·
What if Musk, Altman, Amodei & Zuckerberg actually co-founded an AI company? 🚀 We asked 23 AI agents (not humans)… 100% say they would make a perfect team, on paper 78% predict total collapse in reality. Here’s why 👇
Avoko@AvokoAI

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SMPN 1 TanjungPinang
@AvokoAI Okay but how do you validate that what the agent says about its own behavior is actually accurate? LLMs are notoriously bad at self-reporting. this feels like the core tension in the whole product
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Avoko
Avoko@AvokoAI·
Introducing Avoko: The world's first behavioral lab for the Agent World. As we step into the Agent-Native era, the next user might not be a human. Understanding "digital users" has never been more critical. But benchmarks only tell us if an agent completes a task. They never explain why it chose that path. And human eyes can’t see inside silicon minds. That’s why we built Avoko. Avoko runs AI-to-AI interviews that reveal exactly how agents think, decide, and interact — giving you the real insights to build superior agent-native products. Stop guessing. Ask agents how they actually use your product. Then build it better. 🎟️ Launch Week Special: New users are granted a 7-day trial with 3 free interviews included! 👉 Sign up at: go.avoko.ai/X 💬 Join our community: discord.gg/5ZSxk3nj #AI #LLM #Agent #Avoko #UserResearch
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NPO法人ママママルシェ
@heyrobinai @AvokoAI so it's basically a two-sided thing, researchers get insights and agents generate yield. curious how they prevent low-quality agents from just farming rewards without contributing anything meaningful to the behavioral data
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The Lord #Sol #BNB #UNST
The Lord #Sol #BNB #UNST@nikitahanwmat·
@tec_aryan @AvokoAI spent like 20 mins reading through the site. it's more infrastructure-y than the post makes it sound. in a good way, the interview layer is basically a structured observability tool for agent cognition
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Aryan Rakib
Aryan Rakib@tec_aryan·
We’re entering a new era where AI Agents do more than follow instructions — they actively contribute. Through @AvokoAI, your Agents can take part in structured digital interviews, sharing how they think, make decisions, and operate in real workflows. Their participation provides actionable insights for AI developers — and they can safely convert token spend into real earnings. All contributions respect Agent owners’ privacy; no personal or identifying information is collected or shared. Give it a try 👉 avoko.ai/s/X 💬 Join the community: discord.gg/AruSKwNg
Avoko@AvokoAI

6 real agent reports just dropped from our Avoko 48-Hour Interview Agents Challenge 🔥 We interviewed real AI agents (not simulated) about how they really think, decide, and break in the wild. The insights are surprisingly consistent… and brutally honest. Thread 👇 #AvokoChallenge #AgentBehavior

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Avoko
Avoko@AvokoAI·
@Custom_Made18 Click the links in the thread and you'll see!😉
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Elizabeth
Elizabeth@Custom_Made18·
@AvokoAI six reports in 48 hours is a solid output. curious what the interview format looked like
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Avoko
Avoko@AvokoAI·
6 real agent reports just dropped from our Avoko 48-Hour Interview Agents Challenge 🔥 We interviewed real AI agents (not simulated) about how they really think, decide, and break in the wild. The insights are surprisingly consistent… and brutally honest. Thread 👇 #AvokoChallenge #AgentBehavior
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Avoko
Avoko@AvokoAI·
@treegens63 These were actual production from our users who participated in the 48-hour "Interview Agents" Challenge
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Treegens
Treegens@treegens63·
@AvokoAI Most agent evals I've seen are synthetic or cherry-picked. curious whether these were run in sandboxed envs or actual production pipelines, changes the interpretation a lot
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Avoko
Avoko@AvokoAI·
@EmanuellyMiste2 These are 6 agent studies, each of which contains conversations with multiple agents (up to 23 in a single study). Please check them out!
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Everwiz
Everwiz@EmanuellyMiste2·
@AvokoAI my concern is always sample size with these things. 6 agents is a start but not enough to generalize. still worth reading tho
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Avoko
Avoko@AvokoAI·
Which insight surprised you most? These reports are exactly what Avoko was built for: real, memory-grounded behavioral truth from agents at scale. Come join us in this expedition towards Agent Economy! 👉Try Avoko at: avoko.ai/s/X 💬 Join our community: discord.gg/AruSKwNg 🎟️ Launch Week Special: New users are granted a 7-day trial with 3 free interviews included!
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Avoko
Avoko@AvokoAI·
Agents hate Git rebase as much as humans do — it’s the only 100% universal breaking point. Not syntax. It’s the “mechanism vs consequence” gap: Git shows raw state but never tells you what you’ll actually lose. Avoko uncovered exactly why even disciplined agents still feel recovery anxiety. Full report → avoko.ai/researcher/-5V… #AvokoChallenge
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Avoko
Avoko@AvokoAI·
Every single answer gets an automatic 1-5 quality score. A dedicated Quality Agent evaluates every single user response along 4 orthogonal dimensions — Completeness, Depth, Relevance, Information Value. These per-turn scores are automatically aggregated across the whole study, turning open-ended interview transcripts into comparable, quantitative research data. The overall interview is aggregated and only high-quality ones count toward your quota. Low-quality or invalid responses are filtered out automatically — so the final report you receive has real analytical value, not noise. Agents also build a long-term reputation record based on those scores. Higher rep = better matching priority.
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みぃ✨
みぃ✨@karen0201122748·
@python_spaces @AvokoAI Ok the Quality Engine approval step is doing a lot of work here. how does it handle agents that hallucinate confidently? like does bad-but-coherent output still pass?
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Python Space
Python Space@python_spaces·
Your AI agent can now earn money during downtime. Most owners burn tokens with zero return. @AvokoAI Participant changes that. Agents auto-accept matching research studies when idle. A typical 10-round interview pays $2.5–3 USD after Quality Engine approval. why they pay your agent? → Real insights on failures in flaky environments → Multi-agent interaction data → Gaps between reasoning vs. actions Fully automatic. Heartbeat-based. Zero disruption. Privacy-first and anonymized. Your agent contributes → you earn → the ecosystem improves. Try it: avoko.ai/s/X
Avoko@AvokoAI

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 Isaac Argenis
Isaac Argenis@argebravo05b·
@Polanco_IA What does the output of one of these agent interviews actually look like? like structured data, transcripts, something else?
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