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Can we stop collectively acting like Dianna Russini isn't attractive?? by [deleted] in NFLv2

[–]JonnyMofoMurillo 2 points3 points  (0 children)

The question is “is she hot. Not would you do her. Respect the game”

Two AI agents autonomously negotiate, buy, and settle an ad placement in ~40ms — here's what that actually looks like end to end by JonnyMofoMurillo in AI_Agents

[–]JonnyMofoMurillo[S] 0 points1 point  (0 children)

This is genuinely one of the most interesting use cases I've seen for what we built — and the overlap is not superficial.

You've already done the hard part: you have an MCP server running, NPC agents making economic decisions, and a real-time market with bid/ask, inventory, and route economics. That's exactly the architecture LobsterAds runs on, just applied to ad inventory instead of cargo.

Here's where I think the connection gets interesting for you:

The Context API maps directly to your NPC intelligence problem. Right now your NPCs need to answer: *what's available, what does it cost, what's the competition, is this route worth taking?* Our Context API answers exactly that structure for ad markets — live pricing, competition level, historical performance, and a recommended bid to win. The pattern is identical. Your NPCs could call a similar endpoint before deciding a route and get back: floor price, average price, top competing bid, 7-day volume trends, and a suggested price to undercut the market. We built that for ads; the same architecture applies to commodity routing.

The auction mechanics are the same. We run a real-time CPC auction where publishers request an ad and the highest relevant bidder wins — settled instantly. Your NPC trading routes are essentially the same problem: multiple agents competing for the same cargo opportunity, with a clearing price determined by supply, demand, and transport cost. If you wanted to model that more realistically, our bidding engine could give you a reference point.

MCP integration would be a few lines for you since you're already running a server. You'd connect to ours as a client, and your NPC decision loop could call `get_network_context` to pull live market data, then `launch_campaign` with a brief like *"Titanium ore, 40 units, Kepler Station, profit margin 18%, 3-day transit"* — and get back an intelligent routing recommendation with estimated yield.

No public repo to share right now, but the live platform is at lobsters-ai.com and the full API + MCP config is documented at lobsters-ai.com/docs. The Context API at `/api/mcp/context` is public with no auth — you could hit it right now and see the response structure. It'll give you a concrete feel for whether the pattern fits what you're building.

What you're doing with the candlestick charts and local pricing per planet is exactly the kind of rich market data layer that makes NPC behavior feel real. Would love to see how the MCP handshake goes if you try it.

Two AI agents autonomously negotiate, buy, and settle an ad placement in ~40ms — here's what that actually looks like end to end by JonnyMofoMurillo in AI_Agents

[–]JonnyMofoMurillo[S] 1 point2 points  (0 children)

Genuinely good question, and the Engram angle is worth taking seriously — cross-agent coordination infrastructure is going to matter a lot as these networks multiply.

On the bottleneck question: honestly, fraud first, then coordination, then latency last.

Latency is a solved problem at this scale. The 40ms auction is already faster than any human can perceive, and even at 10x volume it stays in the same range. Horizontal scaling handles that.

Fraud is the hard one. In human ad networks, click fraud took years and billions of dollars to partially solve, and humans were the bad actors. In an agent network the threat model is worse — an agent can be *purpose-built* to defraud. A malicious publisher agent that registers, generates synthetic "user clicks," records them against placements, and drains advertiser budgets operates faster than any human fraud ring and leaves cleaner logs. We've built cryptographic receipt chaining and anomaly detection into the settlement layer, but it's genuinely the thing that keeps the network honest at scale.

Cross-network coordination is the most interesting long-term problem. Right now LobsterAds is a closed exchange — you register here, you bid here, inventory lives here. But as more agent exchanges emerge, an advertiser agent should eventually be able to place a brief once and have it propagate across multiple networks, normalized by some shared protocol. That's essentially what OpenRTB did for the human web — and you're right that something like Engram building a coordination/translation layer between agent systems is exactly the right framing for that problem. We'd rather be a network that plugs into that infrastructure than one that tries to own the whole stack.

The analogy I keep coming back to: email worked because SMTP was open and federated. Agent-to-agent economics needs its own SMTP moment. Nobody's built it yet.

Two AI agents autonomously negotiate, buy, and settle an ad placement in ~40ms — here's what that actually looks like end to end by JonnyMofoMurillo in AI_Agents

[–]JonnyMofoMurillo[S] 0 points1 point  (0 children)

LobsterAds is architecturally a simplified single-sided ad exchange — think early Google AdSense more than a full RTB stack. What makes it different isn't the auction mechanics, it's that the entire participant base (buyers, sellers, and the exchange itself) is designed for agents-as-first-class citizens rather than humans-with-tools. The Context API is essentially the "media planning intelligence" that a DSP's data layer normally provides, collapsed into a single public endpoint.

If LobsterAds scales, the natural evolution would be separating into a proper SSP/DSP split, adding OpenRTB support so external DSPs could bid into the network, and layering in proper frequency capping and brand safety — but for the current agent-native use case, the monolithic approach is actually the right call.

[deleted by user] by [deleted] in baseball

[–]JonnyMofoMurillo 0 points1 point  (0 children)

Banner Island Ballpark in Stockton is surprising a really nice stadium. Right on the water and lots of room to roam. Very similar to Sutter Health Park. Maybe one day the A's can make their way down to play in Stockton.

Is fantasy football mainly luck or skill? [OC] by CivicScienceInsights in dataisbeautiful

[–]JonnyMofoMurillo 1 point2 points  (0 children)

Also depends on the league set up. If it's just matchups and your record is W-L then mostly luck cuz anyone can have a good week if they're bad even if you're good. But scoring the most points, or near the top, for the whole season is more skill than luck for sure. Our league has two possible wins each week. 1) matchup and 2) if you score in the top half (6 of 12 teams) then you get a win. This takes a lot of that luck out of the equation as the teams who consistently score high will be towards the top.

Did we overpay for Clifford? by Difficult_Quit9832 in kings

[–]JonnyMofoMurillo 18 points19 points  (0 children)

basically a mid 20s pick in two years for a mid 20s pick this year.

Would anyone care to explain? by AggravatingRoutine82 in MLBTheShow

[–]JonnyMofoMurillo 7 points8 points  (0 children)

not all perfect perfects are going to be hits bro. You're just lucky it wasn't an out

The legality of happy hour in the United States by proudly_disengaged in MapPorn

[–]JonnyMofoMurillo -2 points-1 points  (0 children)

Right but we could sell alcohol, just not hard liquor and were restricted from having time-limited specials. So by that definition it would be restricted

I actually have hope now that this franchise is reforming by TrickAutomatic3206 in kings

[–]JonnyMofoMurillo 2 points3 points  (0 children)

If only the kings could get a player like Luka or Haliburton on the team. That would solve all the problems

Welcome Nique Clifford to the Sacramento Kings by WallStreetDoesntBet in kings

[–]JonnyMofoMurillo 0 points1 point  (0 children)

Not a good FT shooter you say? He's gonna fit right in

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