🤝
Make a deal with Allan Engelhardt
🔒 Paid proposals held safely in escrow — released only when the work's approved.
Followers
14
Account age
0 yrs
💰 Suggested sponsorship rate
$40 – $65 / sponsored post
Estimated from audience size & typical reach — every deal is negotiable and held in SocialDB escrow.
🧰 Free analysis for Allan Engelhardt
Known for
27 views
@pluralistic makes headlines in the Financial Times, again. Just above a poster of the Supreme Leader of the United States of America, which wasn't and isn't relevant so I cut it out.
https://giftarticle.ft.com/giftarticle/actions/redeem/6352083d-f5ab-4c4e-aa2e-bb77129081e6
2 views
#AI #benchmarks are quietly misleading enterprises.
When engineering reports Model A is "10% more accurate" or Model B has "5% lower latency," it’s easy to assume that translates into business value. It usually doesn't.
Raw capability matters (as we covered yesterday in https://www.linkedin.com/feed/update/urn:li:share:7485235710002872320 ), but P&L metrics don't scale linearly with benchmark scor
📊 Post engagement
6
Avg engagement / post
42.9%
Engagement vs followers
Apr 2026
On Mastodon since
🔥 Top post: @pluralistic makes headlines in the Financial Times, again. Just · 27 likes + reposts
📊 Activity & format
Posting cadence
1 / week
A lower-frequency account — each post lands with more weight.
Content mix
Mostly text
Recent: 8 text · 4 image · 0 video.
Follower / following
0.4×
Follows 40 back. A more reciprocal / networked account.
Recent posts
View on Mastodon ↗
🔥 Top post
@pluralistic makes headlines in the Financial Times, again. Just above a poster of the Supreme Leader of the United States of America, which wasn't and isn't relevant so I cut it out.
https://giftarticle.ft.com/giftarticle/actions/redeem/6352083d-f5ab-4c4e-aa2e-bb77129081e6
🧵 4/4
👉 The Bottom Line
A 10% gap on a model leaderboard is a rounding error on an enterprise P&L **if** your process steps and guardrails remain identical.
Stop shopping for models in a vacuum. Ask: What binary cliff does this technical s…
🧵 3/4
3. Capital Drop-Off (Infrastructure)
Chasing state-of-the-art models on private hardware often leaves expensive GPUs sitting 80% idle just to handle latency spikes. The win isn't peak token speed—it's picking an architecture that let…
🧵 2/4
1. Customer Drop-Off (Latency)
If verification takes 12 seconds, users abandon. At 0.8 seconds, they convert. Shaving latency from 12s to 0.8s changes your business; shaving it from 0.8s to 0.4s doesn't.
2. Touchpoint Drop-Off (Inter…
#AI #benchmarks are quietly misleading enterprises.
When engineering reports Model A is "10% more accurate" or Model B has "5% lower latency," it’s easy to assume that translates into business value. It usually doesn't.
Raw capability matt…
🧵 3/3
1. Accept it: if you absolutely, positively _must_ have the very best models for real-time queries then you have to massively over-provision.
2. Go hybrid: use your own compute for batch processing and cloud API for real-time because…
🧵 2/3
"The reason isn’t bad planning. It’s a mismatch between how standard models generate text and how enterprises actually use them, and text #diffusion is the most interesting candidate for closing the gap. It’s also the most oversold, …
THIS is the clearest explanation I have yet seen on planning your internal #AI #workloads.
"Somewhere in a Singapore data center, a bank is paying for eight H100s that spend most of the night waiting. The cluster was bought for good reason…
"Most vulnerability-management SLAs are organized by severity. Criticals in 15 days, highs in 30, mediums in 90. That structure was built for a world where the count of open criticals was small enough to matter. It’s now actively harmful."…
75% of your AI architecture has no zero competitive value.
Yet, AI teams are misallocating their engineering capital to it.
Many AI rollouts are focused on access to frontier model access and writing custom data connectors.
That is pure pl…
I am late, but happy Labour Day or memorial of St Joseph the Worker to all who celebrate. I give you https://da.wikipedia.org/wiki/Udslidt
The article mentions how the automobile replaced horses without leading to overall economic loss, BUT then says that in the AI economy, **we are the horses**.
#AI #benchmarks are quietly misleading enterprises.
When engineering reports Model A is "10% more accurate" or Model B has "5% lower latency," it’s easy to assume that translates into business value. It usually doesn't.
Raw capability matt…
🧵 3/3
1. Accept it: if you absolutely, positively _must_ have the very best models for real-time queries then you have to massively over-provision.
2. Go hybrid: use your own compute for batch processing and cloud API for real-time because…
🧵 2/3
"The reason isn’t bad planning. It’s a mismatch between how standard models generate text and how enterprises actually use them, and text #diffusion is the most interesting candidate for closing the gap. It’s also the most oversold, …
THIS is the clearest explanation I have yet seen on planning your internal #AI #workloads.
"Somewhere in a Singapore data center, a bank is paying for eight H100s that spend most of the night waiting. The cluster was bought for good reason…
"Most vulnerability-management SLAs are organized by severity. Criticals in 15 days, highs in 30, mediums in 90. That structure was built for a world where the count of open criticals was small enough to matter. It’s now actively harmful."…
75% of your AI architecture has no zero competitive value.
Yet, AI teams are misallocating their engineering capital to it.
Many AI rollouts are focused on access to frontier model access and writing custom data connectors.
That is pure pl…
I am late, but happy Labour Day or memorial of St Joseph the Worker to all who celebrate. I give you https://da.wikipedia.org/wiki/Udslidt
The article mentions how the automobile replaced horses without leading to overall economic loss, BUT then says that in the AI economy, **we are the horses**.
🐘 Community & instance
Home server
mastodon.social
A large general-interest Mastodon server. On the fediverse the server a creator picks hints at their community — this one spans all topics.
On Mastodon since
Apr 2026
An established account with real history on the platform.
💡 Facts
🗓️Joined Mastodon in 2026.
👁️Averages 6 views per post.
📤Posts about 1× per week.
🕵️ Fake follower check
Estimated69/100
Good
Credibility score
92%
Real
Real audience
Low
Fake-follower risk
Medium
Data confidence
- Est. 92% real, active audience · Low fake-follower risk.
- Strong engagement (~0.4× of followers engage each post) — an active, real audience.
Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.
About
Data, business, science.
Why wiknin? Wisdom-Knowledge-Information. https://www.cybaea.net/Journal/2011/01/03/Why/
Opinions here are all my own.
📸 Gallery
🔀 Audience overlap
EstimatedEstimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.
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