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<p style="text-align: justify;"><span style="vertical-align: baseline;">Folding a protein target, screening a 50,000 compound ligand library, or evaluating structure-activity relationships (SAR) are not quick API lookups. They are sustained, stateful, GPU-bound simulations that run for m…+
<p style="text-align: justify;"><span style="vertical-align: baseline;">Building enterprise grade research and development (R&amp;D) agents requires moving past the monolithic assistant model. In this blog post, we will discuss how to use a three-layer architecture: separating cognit…+
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<div class="block-paragraph_advanced"><h3 style="text-align: justify;"><span style="vertical-align: baseline;">A three-layer pattern</span></h3>+
<p style="text-align: justify;"><span style="vertical-align: baseline;">The reference architecture below shows how to architect, optimize, and govern high-compute autonomous agents in biotechnology, specifically Drug Discovery. </span></p></div>+
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<figcaption class="article-image__caption "><p data-block-key="4nr3v">Figure 1 — The three-layer pattern: a cognitive orchestrator (brain), a scalable GPU execution layer (muscle), and an enterprise governance plane.</p></figcaption>+
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<div class="block-paragraph_advanced"><h4><span style="vertical-align: baseline;">The execution layer: scaling the muscle - high-compute execution</span><span style="text-decoration: underline; vertical-align: baseline;"> </span></h4>+
<p style="text-align: justify;"><span style="vertical-align: baseline;">The execution layer is responsible for the heavy scientific computations. The first architectural decision is determining where workloads should run:</span></p>+
<ul>+
<li aria-level="1" style="list-style-type: disc; vertical-align: baseline;">+
<p role="presentation" style="text-align: justify;"><span style="vertical-align: baseline;">Strategic, proprietary pipelines require dedicated GPU infrastructure within your security perimeter</span></p>+
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<li aria-level="1" style="list-style-type: disc; vertical-align: baseline;">+
<p role="presentation" style="text-align: justify;"><span style="vertical-align: baseline;">Routine or standardized workloads can safely be delegated to managed cloud endpoints</span></p>+
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<p style="text-align: justify;"><span style="vertical-align: baseline;">In this architecture, protein folding is driven by </span><a href="https://catalog.ngc.nvidia.com/orgs/nvidia/teams/nim/collections/bionemo-esmfold" rel="noopener" target="_blank"><span style="text-dec…+
<p style="text-align: justify;"><span style="vertical-align: baseline;">A critical hurdle in containerized GPU workloads is the cold-start penalty, the latency delay required to pull multi-gigabyte model weights from an image registry and stage them into GPU memory (VRAM).</span>&l…+
<p style="text-align: justify;"><span style="vertical-align: baseline;">To ensure low latency responsiveness, we build the following as a recommendation into the reference architecture:</span></p>+
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<li aria-level="1" style="list-style-type: disc; vertical-align: baseline;">+
<p role="presentation" style="text-align: justify;"><strong style="vertical-align: baseline;">Maintain warm pools:</strong><span style="vertical-align: baseline;"> Pin the GKE node pool to a minimum of one active node.</span></p>+
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<p role="presentation" style="text-align: justify;"><strong style="vertical-align: baseline;">Preload weights:</strong><span style="vertical-align: baseline;"> Model weights are loaded directly into VRAM at pod initialization, ensuring containers are immediately ready for inf…+
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<p role="presentation" style="text-align: justify;"><strong style="vertical-align: baseline;">Resilient scheduling:</strong><span style="vertical-align: baseline;"> GKE manages pod lifecycles and restarts failed instances without tearing down the underlying VM infrastructure.…+
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<p style="text-align: justify;"><span style="vertical-align: baseline;">This approach trades custom, manual CUDA kernel tuning for NVIDIA's pre-compiled, containerized runtimes, dramatically reducing infrastructure engineering overhead while ensuring deterministic throughput.</span>…+
<p style="text-align: justify;"><span style="vertical-align: baseline;">In biotech, chemical structures represent millions of dollars in proprietary IP. A docking request transmits SMILE strings or 3D coordinate matrices that must never leave company custody.</span></p>+
<p style="text-align: justify;"><span style="vertical-align: baseline;">Containerized NIMs eliminate the friction between rapid prototyping and rigorous data isolation. During early exploration, researchers can query NVIDIA hosted endpoints. When transitioning to proprietary lead candida…+
<h4><span style="vertical-align: baseline;">The cognitive layer: Multi-agent reasoning</span></h4>+
<p style="text-align: justify;"><span style="vertical-align: baseline;">With compute execution isolated, the cognitive layer manages agentic workflow sequencing. Built on </span><a href="https://docs.cloud.google.com/gemini-enterprise-agent-platform/build/runtime"><span st…+
<p style="text-align: justify;"><span style="vertical-align: baseline;">Based on this design, when an end-user submits a high-level task such as </span><strong style="font-style: italic; vertical-align: baseline;">“ Analyze Candidate 4b against Target X and produce a SAR repo…+
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<li role="presentation" style="text-align: justify;"><strong style="vertical-align: baseline;">In-process native agent handoffs: </strong><span style="vertical-align: baseline;">The lead orchestrator delegates tasks to specialist sub-agents using Agent Runtime’s native SDK ra…+
<li role="presentation" style="text-align: justify;"><strong style="vertical-align: baseline;">Passing bulky payloads by reference: </strong><span style="vertical-align: baseline;">LLMs degrade quickly when forced to ingest massive arrays of 3D spatial coordinates. In this ar…+
<li role="presentation" style="text-align: justify;"><strong style="vertical-align: baseline;">Decoupling workflow logic from biochemical reasoning: </strong><span style="vertical-align: baseline;">General-purpose LLMs excel at task planning and synthesis, but are prone to ha…+
<li role="presentation" style="text-align: justify;"><strong style="vertical-align: baseline;">Context-driven evaluation over rigid cutoffs: </strong><span style="vertical-align: baseline;">Traditional computational screening enforces arbitrary numerical cutoffs (e.g., discar…+
</ul>+
<p style="text-align: justify;"><span style="vertical-align: baseline;">By passing disease context directly into the specialized reasoning models, drug candidates are evaluated against dynamic, target-specific profiles rather than static thresholds, preventing the premature culling of vi…+
<h3><strong style="vertical-align: baseline;">Performance best practices for high-compute pipelines</strong></h3>+
<p><span style="vertical-align: baseline;">Optimizing an agentic system that interfaces with heavy GPU compute requires challenging common engineering instincts:<br/><br/></span></p>+
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<p style="text-align: center;"><span style="vertical-align: baseline;">Common Assumption</span></p>+
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<p style="text-align: center;"><span style="vertical-align: baseline;">Architectural Reality</span></p>+
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<p style="text-align: center;"><span style="vertical-align: baseline;">Recommended Best Practice</span></p>+
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<p><span style="vertical-align: baseline;">"Swap in a faster driver model to cut latency."</span></p>+
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<p><span style="vertical-align: baseline;">The primary orchestrator's token generation is rarely the bottleneck in multi-step R&amp;D pipelines.</span></p>+
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<p><span style="vertical-align: baseline;">Optimize I/O, not token speed: Focus on reducing payload sizes and intermediate network hops rather than compromising orchestrator reasoning depth.</span></p>+
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<p><span style="vertical-align: baseline;">"Parallelize tool calls across workers."</span></p>+
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<p><span style="vertical-align: baseline;">External scientific services and containerized models often serialize requests internally on dedicated hardware.</span></p>+
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<p><span style="vertical-align: baseline;">Respect execution topology: Align client-side concurrency with backend queue mechanics to prevent pipeline lockouts and connection timeouts.</span></p>+
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<p><span style="vertical-align: baseline;">"Pass full simulation states between tools."</span></p>+
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<p><span style="vertical-align: baseline;">Large JSON bodies cause schema validation failures, prompt truncation, and token bloat.</span></p>+
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<p><span style="vertical-align: baseline;">Pass heavy payloads by reference: Store raw coordinates in object storage and pass lightweight URIs between agent boundaries.</span></p>+
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<p><span style="vertical-align: baseline;">"Return outputs only when the pipeline finishes."</span></p>+
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<p><span style="vertical-align: baseline;">Long multi-minute runs leave scientists blind to whether jobs are proceeding or stalled.</span></p>+
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<p><span style="vertical-align: baseline;">Stream intermediate stage completions: Emit progress updates at each completed milestone (e.g., </span><span style="font-style: italic; vertical-align: baseline;">folding complete</span><span style="vertical-align: baseline;…+
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<p><span style="vertical-align: baseline;">"Chain multiple granular micro-tools."</span></p>+
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<p><span style="vertical-align: baseline;">Deep tool-chains increase the probability of hallucinated arguments and schema mismatches.</span></p>+
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<p><span style="vertical-align: baseline;">Collapse compute pipelines: Wrap end-to-end simulation pipelines behind a single, clean tool interface that takes clear parameters and returns a consolidated object.</span></p>+
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<h4><span style="vertical-align: baseline;">The enterprise governance and asymmetric autonomy</span></h4>+
<p style="text-align: justify;"><span style="vertical-align: baseline;">Deploying high-compute agents in enterprise environments requires robust data sovereignty, audit trails, and process control. The </span><a href="https://cloud.google.com/blog/products/ai-machine-learning/in…+
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<p role="presentation" style="text-align: justify;"><a href="https://docs.cloud.google.com/iam/docs/agent-identity-overview"><span style="text-decoration: underline; vertical-align: baseline;">Agent Identity</span></a><span style="vertical-align: baseline;">: Ever…+
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<p role="presentation" style="text-align: justify;"><a href="https://docs.cloud.google.com/gemini-enterprise-agent-platform/govern/gateways/agent-gateway-overview"><span style="text-decoration: underline; vertical-align: baseline;">Agent Gateway</span></a><span style…+
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<p role="presentation" style="text-align: justify;"><a href="https://docs.cloud.google.com/gemini-enterprise-agent-platform/govern/agent-registry"><span style="text-decoration: underline; vertical-align: baseline;">Agent Registry</span></a><span style="vertical-align…+
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<p role="presentation" style="text-align: justify;"><a href="https://cloud.google.com/security/products/model-armor?hl=en"><span style="text-decoration: underline; vertical-align: baseline;">Model Armor</span></a><span style="vertical-align: baseline;">: This func…+
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<p style="text-align: justify;"><span style="vertical-align: baseline;">The payoff is clear. Identity, RBAC, auditing, residency, and data protection are native properties of the Gemini platform; this allows enterprise customers to focus on science rather than having to build a complianc…+
<p style="text-align: justify;"><span style="vertical-align: baseline;">In high-stakes research and development, full autonomy introduces unacceptable liability, while requiring approval for trivial steps can create frictions. The solution addressing this to use asymmetric gating in the …+
<p style="text-align: justify;"><strong style="vertical-align: baseline;">Automate reversible operations:</strong><span style="vertical-align: baseline;"> For example, allow the agent to resolve chemical naming synonyms, pull structural PDBs, and run preliminary Lipinski scre…+
<p style="text-align: justify;"><strong style="vertical-align: baseline;">Gate irreversible operations:</strong><span style="vertical-align: baseline;"> For instance, initiating multi-GPU docking run, advancing a lead compound to wet-lab synthesis, or archiving a therapeutic …+
<h3 style="text-align: justify;"><strong style="vertical-align: baseline;">The pattern, and the path forward</strong></h3>+
<p style="text-align: justify;"><span style="vertical-align: baseline;">High-compute autonomous agents succeed when the boundaries between cognitive planning, numerical computation, and system governance are clean in the following ways:</span></p>+
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<p role="presentation" style="text-align: justify;"><span style="vertical-align: baseline;">Keep the orchestrator focused on decomposition and synthesis, leaving intensive biophysical simulation to specialized, containerized microservices and models.</span></p>+
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<p role="presentation" style="text-align: justify;"><span style="vertical-align: baseline;">Eliminate context bloat by passing complex chemical data by reference through cloud storage.</span></p>+
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<p role="presentation" style="text-align: justify;"><span style="vertical-align: baseline;">Anchor the workflow in enterprise governance, pairing cryptographic agent identity with asymmetric human oversight.</span></p>+
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<p style="text-align: justify;"><span style="vertical-align: baseline;">As generative and structural biology models expand toward whole-cell modeling and complex dynamic simulations, this decoupled architecture ensures research systems scale efficiently while keeping proprietary IP secur…+
<p style="text-align: justify;"><span style="vertical-align: baseline;">Reach out to your Google sales representative if you have any requirements to build a use case like this and we will be happy to talk and support you in your agent development journey on Google Cloud.</span><…+
<p><span style="vertical-align: baseline;">Evaluation engineering is a critical foundation for building reliable AI systems. Setting up systematic, repeatable tests to measure your agent’s true behavior can be the difference between shipping a tool you can trust and one that silently bre…+
<p><span style="vertical-align: baseline;">I’ve run evaluation engineering initiatives for years at Google and d</span><span style="vertical-align: baseline;">eveloping the newly released</span><a href="https://cloud.google.com/blog/topics/developers-practitioners/in…+
<p><span style="vertical-align: baseline;">Here are four eval lessons we learned from building the new plugin that you can apply to your own builds.</span></p>+
<h3><span style="vertical-align: baseline;">1. Grade the execution steps instead of the summary</span></h3>+
<p><span style="vertical-align: baseline;">When we first evaluated agents, we set up an LLM-as-judge to inspect the agent’s final text reply and scored it against a checklist. However, we quickly realized it’s fundamentally flawed because the grader only sees what the agent wrote, not wh…+
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<div class="block-paragraph_advanced"><p><span style="vertical-align: baseline;">The grader penalized the agent for doing the right thing simply because it didn’t brag about it in the summary. If your rubric line says "did it run X?", a LLM judge is guessing unless you evaluate the…+
<p><strong style="vertical-align: baseline;">Takeaway</strong><strong style="vertical-align: baseline;">:</strong><span style="vertical-align: baseline;"> Don't grade an agent on its closing pitch. Score the raw execution trajectory to verify what commands were ac…+
<h3><span style="vertical-align: baseline;">2. Design evals for asynchronous operations</span></h3>+
<p><span style="vertical-align: baseline;">When you start reading tool-call trajectories, how you extract that telemetry matters just as much as what you're reading. Extracting agent telemetry into a flattened, sequential list of events obscures concurrent tool dispatch, which is one of …+
<p><span style="vertical-align: baseline;">In our evaluations, when an agent was asked to inspect an environment and look up documentation, the harness dispatched the skill-loading call and two documentation searches simultaneously within a single tool_calls payload. Because activating a…+
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<div class="block-paragraph_advanced"><p><span style="vertical-align: baseline;">The system never gave the skill a dedicated turn to let its guidance influence the agent's actions. If telemetry pipelines strip out turn structures and merge calls into a flat timeline, engineers will…+
<p><strong style="vertical-align: baseline;">Takeaway</strong><strong style="vertical-align: baseline;">: </strong><span style="vertical-align: baseline;">Preserve turn structure in telemetry extractors so you can identify when client-side parallel dispatch issues…+
<h3><span style="vertical-align: baseline;">3. Test live runs and "dry runs" side-by-side</span></h3>+
<p><span style="vertical-align: baseline;">You need to inspect real API calls to catch harness quirks, like parallel dispatch. But if you only test your agent in one environment condition, you're flying half-blind. From day one, you need to run two conditions side-by-side: a live run and…+
<p><span style="vertical-align: baseline;">Live runs frequently hit an unexpected permission error on step two and abort before you ever reach the behavior you’re trying to test. That's why you need the plan-only condition, where you strip credentials and tell the agent to explain what i…+
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