tmuhlestein

6 ms·

1.
We Scaled Platform Support 10x Without Scaling the Team(godaddy.com)
2 points by tmuhlestein 1mo ago|0 comments
2.
A GitHub App Saved Us Hours of Manual Effort(godaddy.com)
2 points by tmuhlestein 1mo ago|0 comments
3.
212k AI coding benchmarks: context beats generic prompts(techloom.it)
2 points by tmuhlestein 2mo ago|0 comments
4.
Building an AI-orchestrated publishing workflow for a long-form writing project
2 points by tmuhlestein 2mo ago|0 comments
5.
GoDaddy Developer Platform for AI Agents(godaddy.com)
2 points by tmuhlestein 3mo ago|0 comments
6.
Routing vs. trust in multi-agent systems(godaddy.com)
2 points by tmuhlestein 6mo ago|0 comments
7.
by tmuhlestein 7mo ago
A lot of the conversation around AI and coding focuses on whether models will replace software engineers. What seems to be happening in practice is slightly different. AI is getting very good at generating code, but the hardest engineering
8.
Dear Software Engineers: You Still Have Value(godaddy.com)
3 points by tmuhlestein 7mo ago|2 comments
9.
by tmuhlestein 7mo ago
One challenge many teams are hitting right now is the gap between AI demos and production AI systems. This AWS case study covers some of the work GoDaddy has been doing to operationalize AI workflows using AWS infrastructure. One example hi
10.
Running production AI systems at scale (GoDaddy and AWS case study)(aws.amazon.com)
3 points by tmuhlestein 7mo ago|1 comments
11.
by tmuhlestein 8mo ago
The interesting part here is publishing agent identity to public DNS rather than keeping it in a closed registry. This separates identity (globally resolvable) from enterprise governance and orchestration.
12.
Publishing AI Agent Identity to DNS (GoDaddy ANS and MuleSoft Agent Fabric)(aboutus.godaddy.net)
1 points by tmuhlestein 8mo ago|1 comments
13.
Fortune: How enterprises are moving from AI pilots to production systems(fortune.com)
1 points by tmuhlestein 10mo ago|1 comments
14.
by tmuhlestein 10mo ago
One consistent pattern in production AI work is that model quality is rarely the main bottleneck. Trust, identity, security, and operational discipline tend to determine whether systems can actually scale beyond pilots—especially as agentic
15.
by tmuhlestein 10mo ago
LLMs are increasingly being used as evaluators — grading outputs, ranking options, and even guiding autonomous agents. But raw model scores are unstable: they drift over time, vary across models, and don’t map linearly to real quality. This
16.
GoDaddy launches ANS API and standards site for verifiable agent identity(aboutus.godaddy.net)
5 points by tmuhlestein 11mo ago|3 comments
17.
by tmuhlestein 11mo ago
GoDaddy just published the Agent Name Service (ANS) API) and an accompanying standards site for defining identity and lifecycle management for autonomous agents. ANS pairs a human-readable name with cryptographically verifiable identity, us
18.
by tmuhlestein 11mo ago
At GoDaddy, our engineering team has been experimenting with how to make AI agents more modular, auditable, and production-ready. Instead of treating agents as monoliths, we designed them around four core tools that separate decision from e
19.
by tmuhlestein 11mo ago
The last few months have proven that autonomous agents are testing the web’s guardrails — from robots.txt to checkout flows — and trust is the casualty. At GoDaddy, we’re addressing this with the Agent Name Service (ANS) open standard — a f
20.
by tmuhlestein 11mo ago
In most ad systems, the logic is simple: highest bid wins. But simple doesn’t mean smart. At GoDaddy, we asked a harder question: Can we optimize both revenue and user satisfaction—without sacrificing either? So, we built DeepAd: a deep lea
21.
by tmuhlestein 11mo ago
Smarter AI Starts with Consensus The next frontier in AI isn’t about bigger models — it’s about smarter collaboration. At GoDaddy, we’re exploring Consensus of LLMs (CoL) — an orchestration approach that brings multiple Large Language Model
22.
by tmuhlestein 1y ago
Innovation doesn’t happen by accident — it happens through experimentation Together with @Marshall Cahill, we shared how A/B testing helps us innovate at GoDaddy and turn bold ideas into a scalable impact. In this piece, we cover how o
23.
Smarter MCP Clients: A Leaner, Faster Approach to LLM Tooling(godaddy.com)
3 points by tmuhlestein 1y ago|1 comments
24.
by tmuhlestein 1y ago
At GoDaddy, we’ve been exploring ways to make large-scale LLM integrations more efficient — not just for us, but for the entire ecosystem. Today, most Model Context Protocol (MCP) clients inject every tool definition into every prompt. That
25.
Building AI Agents from First Principles at GoDaddy(godaddy.com)
2 points by tmuhlestein 1y ago|1 comments
26.
by tmuhlestein 1y ago
Building AI Agents from First Principles at GoDaddy Everyone’s talking about AI agents lately, and for good reason. But at GoDaddy, we’re going deeper: starting from first principles to explore what makes an agent truly robust and usable in
27.
Securing AI agents at the scale of the internet(godaddy.com)
3 points by tmuhlestein 1y ago|1 comments
28.
by tmuhlestein 1y ago
Godaddy just introduced an implementation of the IETF Agent Name Service (ANS) to create trust through an open standard for agent identity and discovery that enables AI agents, businesses, and platforms to securely register, verify, and uni